Eutrophication and Nutrient Cycling in Santa Margarita River Estuary: a Summary of Baseline Studies for Monitoring Order R9-2006-0076

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EUTROPHICATION AND NUTRIENT CYCLING IN SANTA MARGARITA RIVER ESTUARY: A SUMMARY OF BASELINE STUDIES FOR MONITORING ORDER R9-2006-0076

Karen McLaughlin Martha Sutula Jaye Cable Peggy Fong

Technical Report 635 - April 2013 EUTROPHICATION AND NUTRIENT CYCLING IN SANTA MARGARITA RIVER ESTUARY: A SUMMARY OF BASELINE STUDIES FOR MONITORING ORDER R9-2006-0076

Submitted By: Karen McLaughlin and Martha Sutula Southern California Coastal Water Research Project

Jaye Cable Louisiana State University

Peggy Fong University of California, Los Angeles

April 2013

Technical Report 635

Table of Contents Table of Contents ...... i List of Tables ...... iii List of Figures ...... v Executive Summary ...... viii Disclosure ...... xii Acknowledgements...... xii 1 Introduction ...... 13 1.1 Background and Purpose of Report ...... 13 1.2 Report Organization ...... 14 1.3 Site Description ...... 14 1.4 General Study Design ...... 15 2 Patterns in Surface Water and Sediment Nutrients and Primary Producer Communities in the Santa Margarita River Estuary ...... 19 2.1 Introduction ...... 19 2.2 Methods ...... 19 2.2.1 Field Methods ...... 19 2.2.2 Analytical Methods ...... 21 2.2.3 Data Analysis ...... 22 2.3 Results ...... 23 2.3.1 Seasonal and Spatial Trends in Physiochemical Parameters and Nutrients ...... 23 2.3.2 Seasonal Trends in Primary Producers ...... 35 2.3.3 Seasonal Variation in Sediment Grain Size and Total Organic Carbon, Nitrogen and Phosphorus Characteristics by Index Period ...... 38 2.3.4 Seasonal Trends in Sediment Deposition...... 40 2.4 Discussion ...... 42 2.4.1 Summary of Findings ...... 42 2.4.2 Significance of Macroalgae in the SMRE ...... 43 2.4.3 Patterns in SMRE Surface Water and Porewater Nutrient Concentrations and Sediment Bulk Characteristics ...... 45 2.4.4 Significance Sediment Characteristics and Transport in the SMRE ...... 46 3 Estimates and Factors Influencing Benthic Oxygen, Carbon Dioxide and Nutrient Fluxes ...... 47

i 3.1 Introduction ...... 47 3.2 Methods ...... 48 3.2.1 Field Methods ...... 48 3.2.2 Analytical Methods ...... 53 3.2.3 Data Analysis ...... 54 3.3 Results ...... 54 3.3.1 Sediment Porewater Concentrations...... 54 3.3.2 Dissolved Oxygen and Carbon Dioxide Fluxes ...... 57 3.3.3 Nitrogen Fluxes ...... 62 3.3.4 Phosphorus Fluxes ...... 63 3.3.5 Benthic Infaunal Abundance ...... 65 3.4 Discussion ...... 66 3.4.1 Significance of Rates of Benthic Oxygen and Total Carbon Dioxide ...... 66 3.4.2 Seasonal Patterns of Nutrient Fluxes and Benthic Metabolism ...... 69 4 Santa Margarita River Estuary Nitrogen and Phosphorus Budgets ...... 73 4.1 Introduction ...... 73 4.2 Methods ...... 73 4.3 Results and Discussion ...... 76 4.4 Management Options to Reduce Eutrophication ...... 80 5 References ...... 81 Appendix 1 - Quality Assurance Documentation ...... 88 Appendix 2 - Summary of Data to Support Modeling Studies ...... 90 Mass Emissions ...... 90 Sediment Deposition ...... 91 Sediment Bulk Characteristics by Index Period: C, N, P ...... 93 Sediment Porewater Concentrations ...... 95 Water Column Transect Data ...... 97 Primary Producer Biomass and/or Percent Cover ...... 99 Rates of Exchange Between Surface Waters and Sediments – Benthic Flux ...... 100 Data on Additional Factors Controlling Benthic Flux ...... 101 Appendix 3 - Graphs of Segment 1 and Segment 2 2007-2008 Continuous Data ...... 102

ii List of Tables

Table 1.1. Summary of the different sampling activities in the SMRE by time period, types of sampling event, organization and actual dates sampling occurred...... 18 Table 2.1. Annual (Dec-Nov), wet season (Dec-Apr), and dry season (May-Nov) total freshwater discharge at Ysidora USGS Gauge and median air temperature at Oceanside California...... 25

Table 2.2. Mean and standard deviation of Total Nitrogen (TN), Ammonium (NH4), and Nitrate+Nitrite

(NO3+NO2) concentrations in wet (storm) and dry (index) weather periods for ME, Segment 1 (Upstream), and Segment 2 (Downstream)...... 27 Table 2.3. Mean and standard deviation of TP and SRP concentrations in wet (storm) and dry (index) weather periods at ME, Segment 1 (Upstream) and Segment 2 (Downstream)...... 28 Table 2.4. Analyte data for the estuary site and ME site collected during the Bight ‘08 study...... 30 Table 2.5. Comparison of wet macroalgal biomass and percent cover at Segment 1 during TMDL and Bight ‘08 studies...... 36 Table 3.1. Mean and standard deviation of Segment 1 and Segment 2 DO fluxes by index period...... 58 Table 3.2. Spearman’s Rank Correlation among DO, TC02, nutrient fluxes and factors known to influence flux (Temperature – Temp, sediment C:N Ratio (CN), sediment C:P (CP), total infaunal abundance (Infauna), sediment % fines, benthic chl a within chambers (chl a))...... 59 Table 3.3. Nitrogen net fluxes and standard deviations from light and dark chamber fluxes (n=4) by index period...... 62 Table 3.4. Phosphorus net fluxes and standard deviations from light and dark chamber fluxes (n=4) by index period...... 63 Table 3.5. Comparison of fluxes from the Santa Margarita River Estuary to other estuarine environments...... 68 Table 3.6. Denitrification Rates Measured in the Santa Margarita River Estuary Subtidal Sediments on intact cores...... 70 Table 4.1. Summary of nutrient budget terms: sources, losses and change in storage...... 74 Table 4.2. Literature values for Chla:C and C:N:P ratios of primary producer communities and assumptions to convert biomass to areal estimates of N and P associated with biomass...... 75 Table 4.3. Comparison of estimated nitrogen source, loss and change in storage terms in the SMRE during dry weather periods (kg N)...... 76 Table 4.4. Comparison of loads from watershed versus benthic nutrient flux (kg)...... 77 Table 4.5. Comparison of estimated phosphorus source and loss terms in the SMRE during dry weather periods (kg P)...... 78 Table A1.1 QA/QC analysis for the SMRE Data Set...... 89

iii Table A2.1. Summary of mass emission site data by analyte for each storm event...... 90 Table A2.2. Summary of mass emissions data by analyte for each index period...... 90 Table A2.3. 7Be Inventory (I) and mass flux () calculation data...... 91 Table A2.4. Sediment bulk characteristics for each index period...... 93 Table A2.5. Porewater constituent analysis for each index period. Constituent values in µM...... 95 Table A2.6. Transect data for each index period during ebb tide (constituents are in mmol/L, except for chlorophyll a, which is in μg/l)...... 97 Table A2.7. Transect data for each index period during flood tide...... 98 Table A2.8. Means and standard deviations of suspended chlorophyll a and benthic chlorophyll a concentrations during each index period...... 99 Table A2.9. Macroalgae total percent cover and biomass by species during each index period...... 99 Table A2.10. Benthic fluxes by index period and light/dark regime ...... 100 Table A2.11. Number of benthic infauna in each chamber by index period, along with chamber light/dark regime, site average, and standard deviation...... 101

iv List of Figures

Figure 1.1. Conceptual model of sources, sinks and transformations of nutrients into Santa Margarita River Estuary...... 16 Figure 1.2. Location of sampling activities in Santa Margarita River Estuary...... 16

Figure 2.1. Continuous freshwater flow (cfs, log10 scale at Ysidora USGS Station) and Segment 1 water temperature, water level (m), salinity (ppt), and dissolved oxygen (mg L-1) during the Bight ‘08 Eutrophication Study ...... 24 Figure 2.2. Cumulative frequency distribution of dissolved oxygen concentration annually (black line), during wet season (Dec-Apr) and during dry season (May-Oct) at Segment 1 during the Bight ’08 study (2008-2009)...... 25 Figure 2.3. Contour plot (top panel) of Segment 1 DO by month (x axis) and time of day (y axis) relative to water level (bottom ) during the Bight ‘08 study...... 26

Figure 2.4. Mean and standard deviations of concentrations of TN (blue), NH4 (red) and NO3+NO2 (green) at ME (circle), Segment 1 (upstream, square), and Segment 2 (downstream, triangle) as a function of freshwater flow at Ysidora USGS Station (black line)during dry weather index periods...... 27 Figure 2.5. Mean and standard deviations of concentrations of TP (blue) and SRP (red) at ME (circle), Segment 1 (upstream, square), and Segment 2 (downstream, triangle) as a function of freshwater flow at Ysidora USGS Station (black line) during dry weather index periods...... 29 Figure 2.6. Ebb-tide concentrations of N and P along longitudinal transect during dry weather index period...... 31 Figure 2.7. Flood-tide concentrations of N and P along longitudinal transect during dry weather index period...... 32 Figure 2.8. Mixing diagrams (concentration as a function of salinity) of TN (top left), Ammonium (top right), and Nitrate+Nitrate (bottom left) during each of the four index periods...... 33 Figure 2.9. Mixing diagrams of TP (top) and SRP (bottom) concentration (μM) during each of the four index periods...... 34 Figure 2.10. Areal mass of carbon associated with three types of aquatic primary producers (APP) observed Segment 1 in SMRE: phytoplankton, microphytobentos (MPB), and macroalgae. 35 Figure 2.11. Comparison of areal mass of carbon associated with three types of primary producers observed at Segment 1 during TMDL and Bight ‘08 field studies ...... 36 Figure 2.12. 2008 macroalgal and cyanobacterial mat biomass (top panels) and % cover (bottom panels) on intertidal flats for Segment 1 (A and C) and Segment 2 (B and D) by index period...... 37 Figure 2.13. Segments 1 and 2 microphytobenthos (MPB; chl abiomass) by index period...... 38 Figure 2.14. Segments 1 and 2 water column chlorophyll a concentrations by index period...... 38

v Figure 2.15. Relationship between Sediment %OC, %TP and %TN as a function of grain size at Segment 1 (open circles) and Segment 2 (closed circles)...... 39 Figure 2.16. Segment 1 and Segment 2 sediment grain size (as percent fines, ♦), carbon:nitrogen (C:N, ■), and carbon:phosphorus (C:P, ●) core ratios for November 16, 2007, and core ratiosfor each 2008 index period...... 40 Figure 2.17. Total and residual inventories of 7Be (top panels) and new 7Be inventories (bottom panels) are shown versus time from November 2007 thru September 2008 for Segments 1 and 2. . 41 Figure 2.18. Mass flux for Segments 1 and 2 in the Santa Margarita River Estuary...... 42 Figure 2.19. Conceptual model of the relationships between N loading rate and the community composition of primary producers in unvegetated shallow subtidal and intertidal habitat in California estuaries...... 44 Figure 3.1. Graphic depicting how porewater profiles are generated from porewater peepers...... 49 Figure 3.2. Typical chamber time series of dissolved oxygen concentration within the light and dark chambers relative to ambient surface water (Segment 2, July 2008)...... 50 Figure 3.3. Schematic of benthic chamber design as viewed from above...... 51 Figure 3.4. Schematic of benthic chamber design as viewed from side...... 51 Figure 3.5. Flux chambers during deployment...... 52 Figure 3.6. Results of sediment porewater sampling in the Santa Margarita River Estuary Segment 1 (A) and Segment 2 (B) during seasonal index periods; each row represents an index period, first column is total dissolved phosphorus (●) and soluble reactive phosphate (○), second column is nitrate+nitrite (▲) and dissolved organic carbon (■), third column is total dissolved nitrogen (■) and ammonium (□), fourth column is iron (■) and manganese (●), fifth column is sulfide (▲) and total carbon dioxide (●)...... 56

Figure 3.7. Segment 1 light, dark, and net (24-hr average of light and dark) TCO2 fluxes, and estimated C

fixation by index period (A); andlight, dark, and net O2 fluxes, and Gross Primary Productivity (GPP) by index period (B)...... 60

Figure 3.8. Segment 2 light, dark, and net (24-hr average of light and dark) TCO2 fluxes, and estimated C

fixation by index period (A); and light, dark, and net O2 fluxes, and Gross Primary Productivity (GPP) by index period (B)...... 61

Figure 3.9. Segment 1 and Segment 2 benthic NH4, NO3, TDN, DOC, SRP, TDP, Mn, and Fe fluxes for dark (dark grey bands) and light (light grey bands) by index period...... 64 Figure 3.10. Benthic infauna abundance counts for Segment 1 and Segment 2...... 65 Figure 3.11. Pathways for nutrient cycling and decomposition of organic matter in the sediments...... 69 Figure 3.12. Sediment porewater profiles reflect redox status of the sediment...... 71 Figure 4.1. Conceptual model for development of budget estimates...... 73

vi Figure 4.2. Ambient soluble reactive phosphorus versus dissolved inorganic nitrogen (nitrate, nitrite, and ammonium) from transect data taken in the northern channel (transect station # 11-15) and the southern basin (transect station # 1-10)...... 79 Figure A3.1. Continuous water level, salinity, and dissolved oxygen data over December 2007-October 2008 for Segment One (upstream; CDM 2009)...... 102 Figure A3.2. Continuous water level, salinity, and dissolved oxygen data over December 2007-October 2008 for Segment Two (downstream; CDM 2009)...... 103

vii Executive Summary The purpose of this report is to summarize the findings of the Southern California Coastal Water Research Project (SCCWRP) study conducted in the Santa Margarita River Estuary (SMRE) in support of the San Diego Regional Water Quality Control Board (SDRWQCB) Monitoring Order (R9-2006-0076), which requires stakeholders to collect data necessary to develop models to establish total maximum daily loads (TMDLs) for nutrients and other contaminants (e.g. bacteria). SCCWRP, Louisiana State University (LSU) and University of California Los Angeles (UCLA), supported by a Proposition 50 grant from the State Water Resources Control Board (SWRCB), conducted studies in support of model development including monitoring of primary producer biomass, measurement of sediment and particulate nitrogen (N) and phosphorus (P) deposition, measurement of benthic dissolved oxygen (DO) and N and P fluxes, and sediment bulk and porewater N and P. The purpose of this report is two-fold:  Provide a summary of SCCWRP study data that will be used to develop and calibrate the water quality model for the SMRE.  Synthesize study data to inform management actions to address eutrophication and improve the efficiency of nutrient cycling in the SMRE.

Following are the major findings of this study: 1. The SMRE is exhibiting symptoms of eutrophication, as documented by high biomass and percent cover of macroalgae, as well as episodes of low DO. a. Biomass and percent cover of macroalgae were high with a mean averages of 1465 to 1714 g wet wt m-2 over the fall 2008 and 2009 TMDL and Bight ‘08 field studies, and cover up to 100%. No established framework exists to assess adverse effects from by macroalgae, though a recent review (Fong et al. 2011) found studies documenting adverse effects of macroalgae on benthic infauna as low as 700 g wet wt m-2 and with cover greater than 30 to 70%. b. Dissolved oxygen concentrations measured at Segment 1 showed surface waters to be below 5 mg L-1 approximately 19% of the wintertime and 23% of the summertime.

2. High dry season concentrations of dissolved inorganic nutrients indicate anthropogenically- enriched nutrient sources. Four types of data provide evidence for this finding: a. During the summer and fall, little freshwater was delivered to the estuary, yet estuarine

ambient dry season soluble reactive phosphorus (SRP) and ammonium (NH4) were especially

high in Segment 2 (16.1 ±10.1 μM SRP and 29.8 ±19.3 μM NH4) and nitrate (NO3) was high in Segment 1 (69.4 ±29.2) relative to the other San Diego Lagoons in this study. b. Mixing diagrams (plots of salinity relative to nutrient concentrations) of transect data

indicate dry season sources of NO3, phosphate (PO4) and NH4, not associated with direct freshwater input. Lateral inputs of groundwater or, at Segment 2, runoff from holding ponds, may be contributing an unquantified source of nutrients to the estuary.

viii c. Comparison of mass emission sources of NO3 versus benthic influxes of NO3during the

summer and fall show that SMRE surface waters has more NO3 than can be predicted by inputs from the Mass Emission site (ME). These data indicate that there are additional

sources, such as lateral groundwater inputs of NO3. This is a reasonable assumption, given the proximity of intensive, irrigated agriculture that was occurring at the time of sampling and permeable, sandy substrates which dominate the estuary. d. The quantities of N and P required to grow macroalgae during the fall sampling period is not met by measured sources of terrestrial loads nor benthic flux. These data indicate that

there are additional sources, such as lateral groundwater inputs of PO4 that are occurring.

3. During the wet season (Nov- Apr), terrestrial total nitrogen (TN) and total phosphorus (TP) loads were the dominant source of nutrients to surface waters, but during the dry season benthic

NH4and SRP flux dominated measured sources to surface waters and provide nutrients in excess of that required to grow the abundance of macroalgae measured in the estuary. Three types of data are used to support this finding: a. Terrestrial wet and dry weather TN loads were generally balanced, while wet weather dominated annual TP loads (65%). Winter dry weather runoff (Nov-Jan, 41,627 kg TN) represents 36% of the total annual export and 65% of the total dry weather runoff. With respect to TP, 88% of the total annual dry weather runoff (2,882 kg) occurred over the winter and spring index periods. Terrestrial runoff of N and P were during summer and fall were low (535 to 0 kg TN and 328 to 0 kg TP respectively). b. With respect to relative sources, terrestrial TN and TP input overwhelmed all other sources1 during the wet season (Nov-Apr), but during the summer and fall estimated terrestrial input only represented 0 to 25% of TN and TP loads to the surface waters and direct atmospheric deposition is a negligible source. In contrast, benthic flux ranged acted as a sink for about 10% of the terrestrial N and P during the winter index period but then became a dominant source during the summer and fall (>75%), the periods of peak primary producer biomass.

c. During peak periods of macroalgal blooms, benthic fluxes of NH4 and SRP are 1.5 to 19X the N and 0.2 to 4X the P required to grow the abundance of macroalgae observed. Macroalgae is an efficient trap for dissolved inorganic nitrogen (DIN) and has been shown to intercept benthic nutrient effluxes and can even increase the net flux by increasing the concentration gradient between sediments and surface. The storage of large quantities of N and P as algal biomass thus diverts loss from denitrification and burial and providing a mechanism for nutirent retention and recycling within the estuary.

4. The patterns of NH4 and NO3 fluxes suggest that denitrification (loss of NO3 to N gas) may be playing a large role during the winter and spring time when sediments are better flushed and

oxygenated but that dissimilatory nitrate reduction (DNR), the conversion of NO3 to NH4 under anoxic sediment conditions, is clearly a dominant pathway during the summer time and is likely

1 The net exchange of groundwater is unknown.

ix responsible for the large fluxes of NH4 observed during these periods. Thus in the winter and spring, the SMRE is better able to assimilate external DIN inputs through denitrification, but will

be more likely to retain N inputs during the summer and fall as DNR-derived NH4 is incorporated into algal biomass and to some degree retained within the estuary.

5. As a fluvially-dominanted river mouth estuary, the SMRE has an inherent capacity to scour fine- grained sediments, thus making it less susceptible to eutrophication because particulate sources of nutrients such as watershed sediments and decaying organic matter tend to be more quickly exported. Two types of data support this finding:

a. Meaurement of benthic oxygen (O2)fluxes indicated that, on average, estuary net positive

flux of O2 to surface waters in spring to net uptake of O2by sediments in the fall. These rates

of O2 uptake were moderate relative to other eutrophic estuaries. High net total carbon

dioxide (TCO2) effluxes are typically driven by respiration of accumulated dead or decaying biomass (organic matter accumulation) in the sediments rather than respiration of live biomass. b. While the SMRE had among the highest peak biomass of macroalgae documented, this biomass does not appear to accumulate in SMRE sediments from season to season. Surficial sediments were primary sandy, had surface C:N values <10, indicative of algal carbon sources, but these values increased dramatically with depth and with often non-detect with respect to N, indicating that organic matter is not accumulating with depth. In fluvially- dominated river mouth estuaries such as the SMRE, this lack of interannual organic matter accumulation would make them less susceptible to eutrophication and is a factor

responsible for the lower sediment O2 demand, given the high abundances of algal biomass.

Management Options to Reduce Eutrophication The SMRE has the advantage, as a river mouth estuary, that sediments do not appear to have accumulated excessive organic matter with depth. Hypoxia was present in the estuary, but not chronic. Interestingly, both N and P appear to be seasonally limiting in the SMRE. Therefore, options for management of eutrophication in the SMRE are aimed at reducing the availability of nutrients for primary production during the growing season and increasing tidal exchange in order to increase availability of DO and enhance denitrfication. Surface water nutrients were P limited during the winter, and N limited during the summer and fall. Thus management of both N and P sources and the ratios available for primary productivity is critical for managing eutrophication.

Three types of options could be considered: 1) Reduce terrestrial loads in order to limit primary productivity. Emphasis should be placed on reducing both P as well as N from the watershed and lateral inputs. Because sources during the growing season appear to be lateral inputs rather than those estimated by the ME site, minimizing these loads will be a critical and effective management strategy.

2) Increase flushing during peak periods of primary productivity, particularly when SMRE has reduced tidal exchange to surface water exchange with ocean during summer. Clearly this is a

x trade off with the need preserve available tidewater goby habitat during summer. Improved circulation during closed condition could help to limit stratification and therefore ameliorate, to a minor extent, problems with hypoxia.

3) Restoration to improve exchange with expansive area of wetland habitat west of Interstate Highway 5 (I-5). Denitrification rates are typically highest in wetland habitats (Day et al. 1989). Restoration to increase connectivity and exchange of surface waters with the large expanse of

intertidal habitat south of the main channel would help to divert excessive NO3 available during dry season from DNR towards denitrification and permanent loss. This could be accomplished through grading of portions of the natural levee with separates this the central channel from the wetland area.

Future Studies Quantification of additional sources of nutrients such as groundwater to the estuary during dry season is a critical research need, as it will effect TMDL allocations.

xi Disclosure Funding for this project has been provided in full or in part through an agreement with the State Water Resources Control Board. The contents of this document do not necessarily reflect the views and policies of the State Water Resources Control Board, nor does mention of trade names or commercial products constitute endorsement or recommendation for use (Gov. Code 7550, 40 CFR 31.20).

Acknowledgements The authors of this study would like to acknowledge the State Water Resource Control Board Proposition 50 grant program (Agreement No. 06-337-559), which provided funding for this study. We would also like to acknowledge Nick Miller, Stephanie Diaz, Andrew Fields, Jeff Brown, Lauri Green, Toyna Kane and various UCLA undergraduates for assistance with field and laboratory work. We acknowledge CDM, Inc. for their assistance and commitment to field sampling and logistics.

xii 1 Introduction 1.1 Background and Purpose of Report The Santa Margarita River Estuary (SMRE) is a 192 acre estuary located one mile north of the City of Oceanside, in the southwest corner of the Camp Pendleton Marine Corps base. The lower river and estuary have largely escaped the development typical of other regions of coastal Southern California, and are therefore able to support a relative abundance of functional habitats and wildlife, including populations of federally- or state-listed endangered species such as the Least Tern, Western Snowy Plover, Tidewater Goby and Belding’s Savannah Sparrow.

The estuary drains the Santa Margarita River watershed, which encompasses approximately 750 square miles in northern San Diego and southwestern Riverside counties. The Santa Margarita River is formed near the City of Temecula in Riverside County at the confluence of the Temecula and Murrieta Creek systems, one of the fasted growing areas in California. Once formed, the majority of the Santa Margarita River main stem flows within San Diego County through unincorporated areas, the community of Fallbrook, and the Marine Corps Base Camp Pendleton. These urban and agricultural land uses in the watershed resulted in hydrological modifications to the SMRE and have led to increased nutrient loading to the Estuary.

Increased nutrient loads are known to fuel the productivity of primary producers such as macroalgae or phytoplankton in the SMRE, in a process known as eutrophication. Eutrophication is defined as the increase in the rate of supply and/or in situ production of organic matter (from aquatic plants) in a water body. While these primary producers are important in estuarine nutrient cycling and food web dynamics (Mayer 1967, Pregnall and Rudy 1985, Kwak and Zedler 1997, McGlathery 2001, Boyer et al. 2004), their excessive abundance can reduce the habitat quality of a system. Increased primary production can lead to depletion of dissolved oxygen (DO) from the water column causing hypoxia (low

O2) or anoxia (no O2; Valiela et al. 2002, Camargo and Alonso 2006, Diaz and Rosenberg 2008), which can be extremely stressful to resident organisms. An overabundance of macroalgae or phytoplankton can also shade out or smother other primary producers and reduce benthic habitat quality through the stimulation of sulfide and ammonium (NH4) production (Diaz 2001).

As a result of excessive algal abundance and low DO, the SMRE was placed on the State Water Resources Control Board’s (SWRCB) 303(d) list of impaired waterbodies. In order to establish Total Maximum Daily Loads (TMDLs) of nutrients to the estuary, the San Diego Regional Water Quality Control Board (SDRWQCB) issued a Monitoring Order (R9-2006-0076) requiring stakeholders to collect data necessary to develop watershed loading and estuarine water quality models. SMRE stakeholders contracted with CDM, Inc. to collect data on nutrient loading, estuarine hydrology, and ambient sediment and water quality to address the requirements of Investigation Order R9-2006-0076. The Southern California Coastal Water Research Project (SCCWRP), Louisiana State University (LSU) and University of California Los Angeles (UCLA), supported by a Proposition 50 grant from the State Water Resources Control Board (SWRCB), conducted studies to aid model development including monitoring of primary producer biomass, measurement of sediment and particulate nitrogen (N) and phosphorus (P) deposition, measurement of benthic DO and nutrient fluxes, and sediment bulk and porewater

13 nutrients. During October 2007 through October 2008, SCCWRP and CDM conducted field studies to collect the necessary data.

The purpose of this report is two-fold:  Provide a summary of SCCWRP study data that will be used to develop and calibrate the water quality model for the SMRE.  Synthesize study data to inform management actions to address the causes of eutrophication and maximize natural nutrient sinks in the SMRE.

Studies were conducted in order to address the following research objectives: • Characterize the seasonal trends in surface water ambient nutrient concentrations, sediment solid phase and porewater nutrients, and primary producer communities. • Estimate the seasonal and long-term annual deposition of sediments and particulate nutrients to the SMRE • Characterize the seasonal trends in N and P exchange between the Estuary sediments and surface waters (benthic nutrient flux). • Assess the efficiency of nutrient cycling in the SMRE by estimating, to the extent possible, N and P budgets.

1.2 Report Organization This report is organized into an executive summary and four Sections: Executive Summary Section 1: Introduction, purpose, and organization of report, site description, and general study design Section 2: Seasonal trends in SMRE surface water and sediment nutrients and primary producer communities Section 3: Seasonal trends in exchange of nutrients between surface waters and sediments Section 4: SMRE N and P budgets

Appendix 1 provides a summary of quality assurance documentation. Appendix 2 provides data tables summarizing SCCWRP study data (as a complement to graphs used in Sections 2 through 4) to facilitate use of data for modeling.

1.3 Site Description The SMRE is located within the Ysidora Hydrologic Basin of the 750 square mile Santa Margarita Watershed just north of Oceanside California. The Estuary is a 192 acre estuary located in the southwest corner of the Camp Pendleton Marine Corps base. Sixty-seven percent of the estuarine habitat is dominated by mudflats, salt panes and salt marsh habitat, with the remaining 33% as subtidal habitat. The primary source of freshwater input into the estuary is surface flow from the Santa

14 Margarita River, though ancillary freshwater input for the estuary comes from runoff and ground seepage. The estuary is open to the ocean; however flow is constricted by rock jetties from Interstate 5 and railroad crossings. During periods of higher freshwater flow, the ocean inlet is completely open and the main channel of the estuary is intertidal. During periods of lower freshwater flow, the ocean inlet can become partially restricted by sand bars at the mouth, restricting exchange with the ocean reducing tidal flushing.

Prior to 1942, the Santa Margarita floodplain was cultivated for agricultural purposes and until the 1970’s the SMRE was used for military tank training and as a site for the discharge of secondarily treated sewage. Currently this area is designated as a special management zone by the Marine Corps, with no allowances for development. Nutrient sources appear to be predominantly from the watershed and include agriculture, nursery operations, municipal wastewater discharges, urban runoff, septic systems, and golf course operations. Camp Pendleton leases land for agriculture on the headlands north of the estuary, so additional nutrient loading from infiltration and groundwater discharge into the estuary are also possible.

1.4 General Study Design The general study design for all monitoring conducted to support TMDL modeling is based on a basic conceptual model developed to describe the sources, losses, and transformations of targeted constituents within the SMRE (Figure 1.1; McLaughlin et al. 2007). The three principal types of monitoring were conducted: 1. Continuous monitoring of hydrodynamic and core water quality parameters (salinity, temperature, etc.); 2. Wet weather monitoring, which was conducted during and immediately following a specified number of storm events at the mass emission (ME) site in the main tributary, targeted locations in the lagoon, and at the ocean inlet; and 3. Dry weather monitoring, which was conducted during four “index” periods that were meant to capture representative seasonal cycles of physical forcing and biological activity in the estuary. During each index period, sampling was conducted at the ME site and the ocean inlet site, as well as two segment sites within the Estuary. In the SMRE, the Ocean Inlet site represents exchange between the ocean and the lower portion of the Estuary, while the Segment 1 and 2 sites provide information on the mid and upper estuarine reaches.

In general, stakeholder monitoring was intended to cover: 1) continuous monitoring of hydrodynamic and core water quality parameters, 2) all wet weather monitoring, 3) dry weather ambient monitoring of surface water nutrient concentrations within the lagoon and at points of exchange between the lagoon and the ocean inlet and watershed freshwater flows (ME site), and 4) longitudinal transect studies (Figure 1.2).

Figure 1.1. Conceptual model of sources, sinks and transformations of nutrients into Santa Margarita River Estuary. Italics indicate data source used to characterize inputs, outputs and fluxes. Sampling events when these data are collected are given in Table 1.1.

Figure 1.2. Location of sampling activities in Santa Margarita River Estuary.

16 SCCWRP studies collected three types of data: 1) estimates of nutrients associated with sediments and primary producer biomass to complement stakeholder sampling during dry weather index periods, 2) measurements of key rates of exchange or transformation within or among sediments and surface waters, and 3) rates of net sediment and particulate N and P deposition to support sediment transport and estuary water quality modeling. In addition SCCWRP conducted continuous monitoring of water quality parameters and primary producer surveys for a second year following the initial TMDL sampling. Sampling to develop the dataset occurred during four index periods in one year (October 2007 to September 2008; Table 1.1). Each index period represents seasonal variations in the estuary: Storm season (January 2008), post-storm/pre-algal bloom (March 2008), high algal bloom (July 2008), and post-algal bloom/pre-storm (September 2008). This sampling design aimed to provide a means to examine seasonal variability in estuary processes affecting nutrient availability and cycling. SCCWRP sampling was coordinated to coincide with stakeholder monitoring of dry weather ambient water quality (WestonSolutions 2009).

To supplement the TMDL field studies, data collected in the SMRE under SCCWRP’s 2008 Southern California Bight Regional Monitoring Survey (Bight ’08) Coastal Wetland and Estuary Eutrophication Assessment (October 2008-2009) are also summarized in this report. Specifically this includes:  Continuous DO, conductivity, pH, temperature, chlorophyll a (chl a) fluorescence, and turbdity conducted at the Segment 1 site (Interstate Highway 5 (I-5) bridge) at bottom waters  Bimonthly primary producer biomass and percent cover for the following primary producers: microphytobenthos (as benthic chl a), macroalgal biomass and cover, phytoplankton biomass (as water column chl a).  Bimonthly sediment %OC, %N and %P in surface sediments

 Bimonthly dry weather nutrient water samples in the estuary and at the ME site

Methods used to collect these data are given in the Bight ’08 Eutrophication Assessment Quality Assurance Project Plan. The data are summarized in this report for the Santa Margarita River estuary when appropriate.

17 Table 1.1. Summary of the different sampling activities in the SMRE by time period, types of sampling event, organization and actual dates sampling occurred.

Sampling Period Event Organization Date

1/5/08, 1/27/08, Wet Weather Monitoring Storm Sampling (3 storm events) CDM 11/26/08 Wet Weather Monitoring Post Storm Sediment Sampling CDM 12/4/08 Continuous Monitoring Water Quality Monitoring CDM 10/4/07-9/30/08 Interim Period Sediment Deposition LSU 11/15/07 Interim Period Sediment Deposition LSU 12/13/07 Ambient Sampling CDM 1/30-2/8/08 Transect Sampling CDM 2/7/08 Benthic Chamber Study- SEG 1 SCCWRP 1/14/08 Benthic Chamber Study- SEG 2 SCCWRP 1/15/08 Index Period 1 Porewater Peeper Deployment SCCWRP 1/7-1/21/08 Sediment Core SCCWRP 1/21/08 Macroalgae Monitoring UCLA 1/21/08 Sediment Deposition LSU 1/21/08 Interim Period Sediment Deposition LSU 2/28/08 Ambient Sampling CDM 3/24-4/2/08 Transect Sampling CDM 3/27/08

Benthic Chamber Study- SEG 1 SCCWRP 3/26/08

Benthic Chamber Study- SEG 2 SCCWRP 3/27/08 Index Period 2 Porewater Peeper Deployment SCCWRP 3/18-4/3/08 Sediment Core SCCWRP 4/3/08 Macroalgae Monitoring UCLA 4/11/08 Sediment Deposition LSU 4/3/08

TMDL Monitoring TMDL Interim Period Sediment Deposition LSU 5/14/08 Ambient Sampling CDM 7/21-7/30/08 Transect Sampling CDM 7/24/08 Benthic Chamber Study- SEG 1 SCCWRP 7/8/08 Benthic Chamber Study- SEG 2 SCCWRP 7/9/08 Index Period 3 Porewater Peeper Deployment SCCWRP 7/3-7/24/08 Sediment Core SCCWRP 7/24/08 Macroalgae Monitoring UCLA 7/21/08 Sediment Deposition LSU 7/24/08 Interim Period Sediment Deposition LSU 8/20/08 Ambient Sampling CDM 9/23-10/1/08 Transect Sampling CDM 9/25/08 Benthic Chamber Study- SEG 1 SCCWRP 9/24/08 Benthic Chamber Study- SEG 2 SCCWRP 9/25/08 Index Period 4 Porewater Peeper Deployment SCCWRP 9/12-9/30/08 Sediment Core SCCWRP 9/30/08 Macroalgae Monitoring UCLA 9/29/08 Sediment Deposition LSU 9/30/08 12/18/08- Continuous Monitoring Water Quality Monitoring SCCWRP

11/13/09

Bight Sampling 1 Primary Producer Monitoring SCCWRP 11/24/08 Bight Sampling 2 Primary Producer Monitoring SCCWRP 1/20/09 Bight Sampling 3 Primary Producer Monitoring SCCWRP 3/23/09

Bight ‟08 ‟08 Bight Bight Sampling 4 Primary Producer Monitoring SCCWRP 5/18/09 Assessment

Eutrophication Eutrophication Bight Sampling 5 Primary Producer Monitoring SCCWRP 6/26/09 Bight Sampling 6 Primary Producer Monitoring SCCWRP 9/18/09

18 2 Patterns in Surface Water and Sediment Nutrients and Primary Producer Communities in the Santa Margarita River Estuary 2.1 Introduction All estuaries exhibit distinct temporal and spatial patterns in hydrology, water quality and biology that are integral to the ecological services and beneficial uses they provide (Day et al. 1989, Loneragan and Bunn 1999, Caffrey 2004, Rountree and Able 2007, Shervette and Gelwick 2008, Granek et al. 2010). Characterization of seasonal and spatial patterns in surface water and sediment nutrient concentrations and aquatic primary producer communities provides valuable information about the sources, dominant transport mechanisms, and fate of nutrients in the SMRE and helps to generate hypotheses regarding the controls on biological response to nutrients.

The purpose of this Section is to present a baseline characterization of the patterns in surface water and sediment nutrients and aquatic primary producers in the SMRE. This work forms the foundation for interpretation of sediment porewaters and benthic fluxes (Section 3) and characterizing nutrient cycling through N and P budgets for the SMRE (Section 4).

2.2 Methods The following types of field data were collected and methods are explained in detail in this section:  Longitudinal and seasonal trends in surface water ambient nutrient concentrations, conducted in conjunction with CDM  Seasonal trends in aquatic primary producer biomass and/or percent cover and tissue nutrient content

 Seasonal variation in sediment bulk characteristics (grain size, solid phase N and P content) A detailed presentation of the intent and field, analytical, and data analysis methods associated with each of these data types follows below.

When appropriate, ambient water quality data collected and analyzed by CDM are incorporated into the results and discussion. These data are cited when used and for a detailed explanation of methods, see CDM (2009).

2.2.1 Field Methods 2.2.1.1 Surface Water Nitrogen and Phosphorus Along a Longitudinal Gradient Longitudinal transects of surface water nutrient concentrations provide valuable spatial information about how concentrations vary along a gradient from the freshwater source to the ocean (or in this case river) end-member.

Surface water samples were collected by CDM at 12 sites along a longitudinal transcect of the SMRE (Figure 1.1; CDM 2009). Longitudinal transect sampling occurred on the fourth day of the first week of each index period. Transect sampling was performed using kayaks and grab-sampling techniques.

19 Sampling occurred in the main channel and samples were collected once at ebb tide and once at flood tide.

The sample bottle was triple rinsed with lagoon water before filling completely with surface water. Sample bottles were open and closed under water to avoid contamination with surface films or stratified water masses. One liter sample bottles were returned to the shore for immediate filtering where appropriate. Ambient water samples were subsampled for a suite of analytes (total nitrogen (TN), total phosphorus (TP), total dissolved nitrogen (TDN), total dissolved phosphorus(TDP), nitrate

(NO3), nitrite (NO2), NH4, soluble reactive phosphorus (SRP), dissolved organic carbon (DOC), iron (Fe) and manganese (Mn)) using a clean, 60 ml syringe. Each syringe was triple rinsed with sample water. Mixed cellulose ester (MCE) filters were used for nutrient analysis and polyethersulfone (PES) filters were used for DOC and metals analysis. Each filter was rinsed with ~20 ml of sample water (discarded) before collection into vials.

2.2.1.2 Inventory of Aquatic Primary Producer Cover and Tissue Content Aquatic primary producer communities include macroalgal and cyanobacteria mats, benthic algal mats, suspended phytoplankton, and submerged aquatic vegetation (SAV). The purpose of this study element was to characterize seasonal variation in the standing biomass, cover, and the tissue nutrient content of these communities. This information will be used to calibrate the component of the eutrophication water quality model that accounts for the storage and transformation of nutrients in primary producer community biomass.

Aquatic primary producer biomass was measured during the four index periods at the two segment sites at low tide. At these sites, intertidal macroalgae were sampled along a 30-m transect parallel to the waterline and one meter down-slope from the vascular vegetation. Macroalgal abundance was determined by measuring percent cover and algal biomass; including both attached and detached mats. At 5 randomly chosen points along each transect, a 0.25-m2 quadrat with 36 evenly spaced intercepts (forming a 6X6 grid) was placed on the benthos. The presence or absence of each macroalgal species in the top layer under each intercept was recorded. Percent cover was calculated from the number of points where algae was covered, divided by the total number of points possible. When present, algae were collected from a 530.9 cm2 area circumscribed by a plastic cylinder placed on the benthos in the center of each quadrat. Each sample was placed in an individual ziploc bag in a cooler, transported to the laboratory and refrigerated.

In the laboratory, algal samples were transferred to low nutrient seawater where they were cleaned of macroscopic debris, mud and animals. For each sample, algae were placed in a nylon mesh bag, spun in a salad spinner for one minute, wet weighed, rinsed briefly in deinonized water to remove salts, and dried at 60°C to a constant weight. Macroalgal biomass was normalized to area (g wet wt m-2). Fine macroalgal filaments that grow within the sediment may be visible but biomass cannot be collected quantitatively at this early growth stage, making percent cover in this case a more sensitive measurement. In addition, when there is 100% cover, and mats are different thicknesses, biomass will be a more useful measure to make distinctions between sites (Sfriso et al. 1987). Thus it is important to use both methods to estimate abundance. Samples were cleaned and weighed to determine wet and

20 dry weights. Dried samples were analyzed for percent organic carbon (%OC), percent organic N and percent P.

2.2.1.3 Sediment Bulk Characteristics and Solid Phase Nutrients All sediments carry nutrients, either as organic matter or, in the case of P, associated with particles. When deposited in the estuary, these particulate nutrients may break down to biologically available forms and may build up in high concentrations in sediment porewaters. Sediment bulk characteristics control nutrient content; finer particle size fractions are associated with higher organic carbon (OC), N and P content (Sutula et al. 2006).

The purpose of this study element was to characterize the inventories of nutrients associated with sediments. Specifically, this involved measurement of the sediment solid phase bulk characteristics (grain size, porosity, etc.) and sediment OC, N and P concentrations.

Sediment bulk characteristics and solid phase nutrient concentrations were estimated for a vertical profile in one sediment core taken from each segment site per index period. For each sampling period, one sediment core was taken and vertically sectioned on site into 1 cm intervals from the sediment water interface until 6 cm depth and then sectioned every 2 cm down to 12 cm. Sediments were placed in plastic storage bags and stored on ice in the dark until they reached the laboratory. In the lab, sections were wet weighed, dried at 50C to a constant weight, and reweighed to determine percent solids and wet bulk density. A subsample of each section (~10 grams dry weight) was removed and ground to a fine powder for %OC, percent total nitrogen (%TN) and percent total phosphorus (%TP) analysis. The remainder of the section was utilized for grain size analysis (percent fines).

2.2.2 Analytical Methods All water samples were assayed by flow injection analysis for dissolved inorganic nutrients using a

Lachat Instruments QuikChem 8000 autoanalyzer for the analysis of NH4, NO3, NO2, and SRP. Dissolved Fe and Mn were measured by atomic adsorption spectrophotometry on a Varian Instruments AA400. Water samples were assessed for TDN, TDP, TN and TP via two step process: first water samples undergo a persulfate digest to convert all N from all N compartments into NO3 and the P from all P compartments into orthophosphate; then the resulting digests are analyzed by automated colorimetry (Alpkem or Technicon) for nitrate-N and orthophosphate-P (Koroleff 1985). Water DOC was analyzed on a Shimadzu TOC-5000A Total Organic Carbon Analyzer with ASI-5000A Auto Sampler. Water total carbon dioxide (TCO2) was analyzed on a UIC instruments carbon dioxide coulometer. Inorganic nutrients analyses were conducted by the Marine Science Institute at the University of California, Santa Barbara; TDN, TDP, TN, and TP analyses were run at the University of Georgia Analytical Chemistry Laboratory.

Dried sediment samples were subsampled and ground for analysis of %OC, %TN, and %TP. Samples for %OC were acidified to remove carbonates; %OC and %TN were measured by high temperature combustion on a Control Equipment Corp CEC 440HA elemental analyzer at the Marine Science Institute, Santa Barbara. Sediment %TP were prepared using and acid persulfate digest to convert all P to

21 orthophosphate, which was then analyzed by automated colorimetry (Technicon) at the University of Georgia Analytical Chemistry Laboratory.

To determine percent fines, a portion of sediment from each interval was weighed dry (total dry weight), then wet sieved through a 63 µm sieve, dried at 50 C to a constant weight, and reweighed as sand dry weight. Percent sand was calculated as a function of the sand dry weight divided by the total dry weight of the sample. Percent fines were calculated as the total weight minus the percent sand.

2.2.3 Data Analysis Analysis of variance (ANOVA) tests were used to test for differences in concentration by index period and, where relevant, by ebb and flood tide (SAS Proc GLM, 2008). Data were transformed to correct for unequal variance and mean and standard errors were generated from Tukey’s pairwise comparisons.

Standing biomass of aquatic primary producers groups (phytoplankton, macroalgae, microphytobenthos (MPB), and cyanobacteria mats) were converted to carbon per meter squared in order to make comparisons among the groups. The following assumptions were used in this conversion:

 Phytoplankton- Average 1.5 m depth of water, chl a: C ratio of 30 (Cloern et al. 1995)

 MPB – chl a: C ratio of 30:1 (Sundbäck and McGlathery 2005)  Cyanobacteria: 50% C by dry wt (study data)

 Macroalgae: 22% C by dry wt (study data)

Porosity, fractions of water and sediment, and wet bulk density were used to estimate seasonal and annual sediment deposition rates and to evaluate changes in sediment nutrient and radioisotope inventories. These values are calculated from parameters measured in the laboratory.

The difference between wet and dry weights was used to calculate the fraction water (fwet) and fraction sediment (fdry):

Wwet  Wdry f wet  Wwet Eq. 2.1, 2.2 f dry  1  f wet

where Wwet and Wdry are the wet and dry sediment weights, respectively. Subsequently, when enough sample was present, a small known fraction of the initial dried sample was weighed, and dry grain density was determined gravimetrically using Archimedes principle, i.e. by volume displacement. The weighed sediment divided by the displaced volume yielded the dry grain density of each sediment core sample section. The dry grain density and fractions wet and dry were used in turn to calculate the porosity and bulk density. Often the shallowest sections of the cores did not contain enough material for a complete sediment physical properties analysis. We took extra cores near the end of the project to complete any missing sediment physical property data needed for future calculations. Porosity is a

22 measure of the amount of “empty space” in the sediment, defined by the ratio of the volume of voids to the total volume of a rock or unconsolidated material. Porosity was calculated using the following equation:

f wet    water Eq. 2.3 f f dry wet  water drygrain

where  is the porosity; water and drygrain are the density of ambient water and dry sediment grains, respectively. Bulk density, wetbulk or drybulk, was calculated based on the total mass of each core section divided by the core section interval volume. Thus both a wet and a dry bulk sediment density could be determined on deeper samples more often when a larger mass of sample was available for the different analyses. Wet bulk density ( in g cm-3) is given by the Equation 2.4.:

Eq. 2.4

Where WSEDwet (i) is the wet weight of each sediment core section interval and V is the volume of the sediment core section interval.

2.3 Results 2.3.1 Seasonal and Spatial Trends in Physiochemical Parameters and Nutrients Continuous data from Segment 2 (upstream) and Segment 1 (downstream) during the 2007-2008 sampling season had quality assurance problems (see Figures A3.1 and A3.2 in Appendix 3), and thus are not utilized in the data analysis. Data from the Bight ‘08 Eutrophication Assessment collected during 2008-2009 are presented in order to describe general patterns of hydrology.

Water quality and primary producer biomass would be expected to change as a function of estuary hydrology, salinity, pH and temperature. Figure 2.1 shows SMRE water level, salinity and DO as a function of freshwater flow into the estuary during Bight ‘08 at Segment 1 (at I-5 Bridge). During the wet season (December 2008-April 2009), freshwater base flow at the Ysidora USGS station averaged 10 cfs, with two large storms (peaks of 500 to 1000 cfs) occurring in mid-december 2008 and February 2009. Tidal range during this time period is 1.4 m, and salinity fluctuates from 0 to 32 ppt, indicating that the estuary mouth is open and fully tidal. Temperatures range 10 to 20 oC, with mean monthly temperatures increasing from 14 to 16 oC over this period. With the onset of the dry season (May- October 2009), freshwater base flow gradually reduces to zero. Minimum water levels increase by 0.5 m but retain a strong tidal signal, indicating the restriction, but not closure, of the estuary mouth. Salinities show a decreased influence of freshwater as difference between the daily minima and maxima range from 20 ppt in May to 2 ppt in August. Water temperatures during this period range from 15 to 25oC, with peak temperatures in July and August.

10000

1000

100

of Freshwater Freshwater of 1

10 0.1

log (cfs) Ysidora @ Flow

0.01 12/1/200835 1/1/2009 2/1/2009 3/1/2009 4/1/2009 5/1/2009 6/1/2009 7/1/2009 8/1/2009 9/1/2009 10/1/2009 11/1/2009

Water Temperature (oC) WaterTemperature 5 1.8 12/1/2008 1/1/2009 2/1/2009 3/1/2009 4/1/2009 5/1/2009 6/1/2009 7/1/2009 8/1/2009 9/1/2009 10/1/2009 11/1/2009 1.6 1.4 X Data 1.2 1.0 0.8 0.6 0.4

Water(m) Level 0.2 0.0 -0.2 12/1/200840 1/1/2009 2/1/2009 3/1/2009 4/1/2009 5/1/2009 6/1/2009 7/1/2009 8/1/2009 9/1/2009 10/1/2009 11/1/2009 X Data 30

Salinlity (ppt) Salinlity 0

12/1/200820 1/1/2009 2/1/2009 3/1/2009 4/1/2009 5/1/2009 6/1/2009 7/1/2009 8/1/2009 9/1/2009 10/1/2009 11/1/2009 X Data 15

Dissolved Oxygen (mg/L) Oxygen Dissolved Dec-08 Jan-09 Feb-09 Mar-09 Apr-09 May-09 Jun-09 Jul-09 Aug-09 Sep-09 Oct-09 Nov-09 Time

Figure 2.1. Continuous freshwater flow (cfs, log10 scale at Ysidora USGS Station) and Segment 1 water temperature, water level (m), salinity (ppt), and dissolved oxygen (mg L-1) during the Bight „08 Eutrophication Study (McLaughlin 2012). Green and red lines in dissolved oxygen graph show the SDREWQCB 5 mg L-1 basin plan objective and the 2 mg L-1 definition of hypoxia (Diaz 2001), respectively.

24 Between study years, total freshwater flow was 60% higher and median dry season air temperatures (as a proxy for insolation) was 2oF higher in 2007-2008 then in 2008-2009 (Table 2.1).

Table 2.1. Annual (Dec-Nov), wet season (Dec-Apr), and dry season (May-Nov) total freshwater discharge at Ysidora USGS Gauge and median air temperature at Oceanside California. Air temperature is a proxy for insolation.

Period 2007-2008 2008-2009 Dicharge (cf) Median Air Temp. (°F) Discharge (cf) Median Air Temp. (°F)

Annual 1.32E+09 61 8.27E+08 62 Wet Season 1.26E+09 54 7.84E+08 55 Dry Season 6.78E+07 69 4.27E+07 67

Dissolved oxygen concentrations averaged 7 mg L-1 during the Bight ‘08 field study, with instantaneous concentrations below 5 mg L-1 , a level considered biologically stressful, approximately 23% of the time during the period of record (December 2008-November 2009; Figure 2.2). The percentage of time below 5 mg L-1 was slightly higher during the summer (25%) versus winter (19%), coincident with higher water temperatures, reduced tidal exchange and decreased freshwater flow (Figure 2.1). Concentrations of < 5 mg L-1 typically occurred in pre-dawn hours and coincided with periods of low tidal flushing during neap tidal cycles (Figure 2.3).

1.0

0.9

0.8

0.7

0.6

0.5

0.4

Proportion of Time 0.3 Dec 2008-Nov 2009 Wet Season (Dec - April) 0.2 Dry Season (May-Oct)

0.1

0.0 0 5 10 15 20

Dissolved Oxygen Concentration (mg/l)

Figure 2.2. Cumulative frequency distribution of dissolved oxygen concentration annually (black line), during wet season (Dec-Apr) and during dry season (May-Oct) at Segment 1 during the Bight ‟08 study (2008-2009).

25 22 20 20 19 18 18 17 16 16 15 14 14 13 12 12 11 10 10 9 8

8 7 Time of Day (hr) Day Timeof 6 6 5 4 4 3 2 2 1 0

39814 39844.5 39875 39905.5 39936 39966.5 39997 40027.5 40058 40088.5 1.8 1.6 1.4 1.2 1.0 0.8 0.6

Water Level (m)Level Water 0.4

Water Level (m) WaterLevel 0.2 0.0 -0.2 1/1/2009 2/1/2009 3/1/2009 4/1/2009 5/1/2009 6/1/2009 7/1/2009 8/1/2009 9/1/2009 10/1/2009 11/1/2009 Jan Feb Mar Apr May X Data Jun Jul Aug Sep Oct Month (Dec 2008-Oct 2009)

Figure 2.3. Contour plot (top panel) of Segment 1 DO by month (x axis) and time of day (y axis) relative to water level (bottom ) during the Bight „08 study. Legend on right shows color key for DO concentration. Contour line represents concentrations <5 mg L-1.

During the 2007-2008 field study, several consistent patterns emerged with respect to ambient wet and dry weather N concentrations (Table 2.2; Figure 2.4). First of all, average wet weather TN concentrations (151±41 μM or 2.1±0.5 mg L-1 TN) were almost always lower than dry weather concentrations (234 ±273 μM or 3.3±3.6 mg L-1 TN). During wet weather, TN concentration ranged from 152 to 159 μM (2.1 to 2.2 mg L-1) at the ME site, and 97 to 231 μM (1.4 to 3.2 mg L-1) at the estuary segment sites. These values are significantly above basin plan objectives for TN (1 mg L-1). During this time, the ME site generally had higher NH4 content (16%) than the Segment sites (2 to 6%), while

Nitrate+Nitrite (NO3+NO2) concentrations generally ranged from 48 to 77% of TN among ME and Segment sites. During dry weather during the 2008-2009 study, TN had similar average values to the 2007-2008 study but wider ranges. Total nitrogen at the ME station ranged 23 to 223 μM (0.32 to 3.1 mg L-1) TN, while within the estuary, the range was greater, 57 to 971 μM (0.8 to 13.6 mg L-1) TN. During this time, ME station TN was always lower than Segment 1 concentrations (downstream) by roughly a factor of 5, and roughly equal to Segment 2 concentrations. This pattern was also typical of NH4 and NO3+NO2. Dry weather ME and estuary Segment 1 stations generally had lower NH4 content (3 to 6% TN) relative to

Segment 2 (23% TN), while NO3+NO2concentrations ranged from 33 to 65% of TN among ME and estuary sites. In general, the higher NH4 (23 μM) and low NO3+NO2 (16 μM) were observed at estuary Segment 2 (upstream of I-5 bridge) during the end of the dry season (July and September 2008;) while

Segment 1 (downstream of I-5 bridge) had opposite trends (5 μM NH4 and 67 μM NO3+NO2).

Table 2.2. Mean and standard deviation of Total Nitrogen (TN), Ammonium (NH4), and Nitrate+Nitrite (NO3+NO2) concentrations in wet (storm) and dry (index) weather periods for ME, Segment 1 (Upstream), and Segment 2 (Downstream). All concentrations in μM.

Event Site Date TN NH4 NO3+NO2 Storm 1 ME 1/5/2008 152.0±123.2 0.9±0.6 84.1±93.7 Seg 2 1/5/2008 142.8±62.6 11.5±4.8 67.5±56.5 Seg 1 1/5/2008 122.9±68.3 1.7±1.4 90.0±56.6 Storm 2 ME 1/27/2008 159.7±28.0 48.7±45.3 90.4±23.8 Seg 2 1/27/2008 97.3±17.2 2.9±0.0 47.9±0.0 Seg 1 1/27/2008 231.8±11.0 6.3±0.0 189.1±0.0 Index 1 ME 1/31/2008 223.8±40.2 2.2±1.9 194.3±43.4 Seg 2 1/31/2008 205.4±11.7 15.1±16.1 166.6±27.6 Seg 1 1/31/2008 971.1±1246.4 20.3±12.8 831.5±845.4 Index 2 ME 3/24/2008 80.1±10.5 10.3±12.5 52.7±3.0 Seg 2 3/24/2008 60.5±9.4 8.0±5.7 26.9±12.2 Seg 1 3/24/2008 566.0±906.4 12.5±11.0 518.6±909.8 Index 3 ME 7/21/2008 23.2±3.6 0.6±0.3 0.6±0.0 Seg 2 7/21/2008 61.3±9.3 12.9±19.2 1.5±0.8 Seg 1 7/21/2008 164.0±60.3 5.0±2.8 95.5±37.3 Index 4 ME 9/23/2008 No data Seg 2 9/23/2008 57.1±9.6 29.8±19.3 1.6±0.7 Seg 1 9/23/2008 164.9±147.8 5.6±6.6 37.5±48.5

Several consistent patterns also emerged with respect to ambient wet and dry weather P concentrations during the 2007-2008 field study (Table 2.3; Figure 2.5). First of all, wet weather average TP

27 concentrations (8.0±2.3 μM or 0.25±0.1 mg L-1 TP) were generally equivalent to dry weather concentrations (7.3 ±4.3 μM or 0.23±0.1 mg L- TP). During wet weather, TP ranged from 6 to 10 μM (0.2 to 0.3 mg L-1) at the Mass Emission site, and 5 to 11 μM (0.2 to 0.3 mg L-1) at the Segment sites. Similar to TN, these values are significantly greater than the Basin Plan objective of 0.1 mg L-1 TP. During this time, the ME site generally had a lower SRP content (44% of TP) than the estuary segment sites (60 to 80% of TP), indicating that the particulate fraction was higher at the ME site. During 2008-2009 dry weather index periods, ME station TP ranged 4 to 6 μM (0.1 to 0.2 mg L-1), while within the estuary, the range was greater (4 to 19 μM or 0.1 to 0.6 mg L-1TP). During the winter and spring index periods, ME station TP was half of that of Segment 1 concentrations (downstream of I-5 bridge) and roughly equal to Segment 2 concentrations (upstream of I-5 bridge). This pattern was also typical for SRP. During the summer and fall index periods, Segment 2 had the highest concentration of TP and SRP, with concentrations two to five times higher than the ME site. During dry weather, the ME and Segment sites generally had SRP concentrations as a percent of TP within the same range (58 to 60% of TP).

Table 2.3. Mean and standard deviation of TP and SRP concentrations in wet (storm) and dry (index) weather periods at ME, Segment 1 (Upstream) and Segment 2 (Downstream). All concentrations in μM.

Event Station Date TP SRP Storm 1 ME 1/5/2008 6.3±4.1 3.0±1.5 Seg 1 1/5/2008 5.4±2.4 4.1±1.9 Seg 2 1/5/2008 8.7±0.6 6.1±0.3 Storm 2 ME 1/27/2008 10.3±4.4 4.2±2.1 Seg 1 1/27/2008 10.5±11.7 4.8±0.0 Seg 2 1/27/2008 6.8±4.8 7.2±0.0 Index 1 ME 1/27/2008 4.3±1.1 3.5±1.0 Seg 1 1/27/2008 9.2±6.2 6.5±1.2 Seg 2 1/27/2008 4.5±0.9 3.1±0.9 Index 2 ME 3/24/2008 4.3±0.5 1.9±0.7 Seg 1 3/24/2008 9.4±7.5 6.7±5.8 Seg 2 3/24/2008 4.3±0.7 1.7±0.6 Index 3 ME 7/21/2008 6.4±0.9 3.0±0.4 Seg 1 7/21/2008 5.4±0.5 2.7±0.9 Seg 2 7/21/2008 9.3±2.0 4.7±2.0 Index 4 ME No data Seg 1 9/23/2008 4.3±0.7 1.8±1.0 Seg 2 9/23/2008 19.3±7.2 16.1±10.2

Figure 2.5. Mean and standard deviations of concentrations of TP (blue) and SRP (red) at ME (circle), Segment 1 (upstream, square), and Segment 2 (downstream, triangle) as a function of freshwater flow at Ysidora USGS Station (black line) during dry weather index periods. Data from CDM (2009).

Spatially, trends were visible along a longitudinal gradient in the SMRE (Figures 2.6 and 2.7) and were consistent with trends observed during daily index period samples (Table 2.3 and 2.4). During flood tides, concentrations of TP and SRP increase from near the mouth upstream for most index periods (Figure 2.7). These patterns are less clear, but still visible during ebb tides (Figure 2.6). Slight increases in upstream are visible with TN and dissolved inorganic nitrogen (DIN = NH4 and NO3+NO2) for the spring index period and for TN during the fall index period. Mixing diagrams (plots of salinity relative to nutrient concentrations) are helpful in interpreting the extent to which freshwater versus marine endmembers are the primary source of nutrient and to what extent within estuary sources (e.g. storm drains, groundwater, benthic flux, biological release) or sinks (benthic flux, denitrification, biological uptake) are visible. Figures 2.8 and 2.9 show that for January

2008 index period, NO3+NO2and SRP drive the overall patterns in TN and TP respectively, and that in both cases there appears to be a source of these NO3+NO2and SRP in the 0 to 5 ppt region, while NH4 appears to have a source in the 10 to 20 ppt region of the estuary.

During the March index period, NO3+NO2drives trends in TN, which increases towards the freshwater endmember. Nitrate+nitrite appears to be fairly conservative over the salinity gradient. However, production of NH4 appears to be occurring over the 0 to 30 ppt range. SRP and TP likewise show an increase towards the freshwater endmember, with a slight convex shape indicating production in the zone 0 to 15 ppt.

29 During both the July and September 2008 index period, the salinity range was limited because of little to no freshwater input. Total Nitrogen decreased slightly with increasing salinity, with mmonia appeared to drive TN concentrations, with a zone of production in 32 to 36 ppt. In contrast, NO3+NO2 concentrations were generally flat, indicating a sink, with the exception of production around 32 to 36 ppt. SRP and TP showed similar trends to TN, with a zone of production likewise around 32 to 36 ppt.

Table 2.4. Analyte data for the estuary site and ME site collected during the Bight „08 study.

Sample Site Analyte (uM) Date SRP NO2 NO2+ NO3 NH4 TN TP TDN TDP 11/24/08 5.2 0.1 1.4 3.4 53.7 8.2 38.5 6.2 2/3/09 2.6 ND 0.9 1.5 17.0 4.3 15.7 3.7 3/23/09 3.1 0.1 0.3 0.6 39.9 4.7 24.1 5.1 Estuary 5/18/09 0.4 ND 0.4 0.2 90.0 11.3 21.4 3.6 6/26/09 4.5 ND 0.6 0.5 33.2 13.4 25.1 10.0 9/18/09 0.4 ND 2.5 0.6 21.7 11.1 15.6 10.3 11/24/08 70.9 8.2

2/3/09 22.0 4.1

3/23/09 21.7 2.4 ME 5/18/09 144.3 2.9

6/26/09 29.8 10.2

9/18/09 10.1 ND ND 0.9 35.4 15.0 13.7 10.6

300 20 16 300 14 250 250 15 12 200 200 10 150 10 150 8

TP (uM)

TN (uM) TN

DIN (uM) DIN 6 (uM) SRP 100 100 4 5 50 50 Index Period Winter 1 - 2 0 0 0 0 300 20 16 300 14 250 250 15 12 200 200 10 150 10 150 8

TP (uM)

TN (uM) TN

DIN (uM) DIN 6 (uM) SRP 100 100 4 5

Index Period Spring 2 - 50 50 2 0 0 0 0 300 20 16 300 14 250 250 15 12 200 200 10 150 10 150 8

TP (uM)

TN (uM) TN

DIN (uM) DIN 6 (uM) SRP 100 100 4 5 50 50 2

Index Period Summer 3 - 0 0 0 0 300 20 16 300 14 250 250 15 12 200 200 10 150 10 150 8

TP (uM)

TN (uM) TN

DIN (uM) DIN 6 (uM) SRP 100 100 4 5 50 50

Index Period Fall 4 - 2 0 0 0 0 1 3 5 7 9 11 1 3 5 7 9 11 Transect # Transect # DIN SRP TN TP

Figure 2.6. Ebb-tide concentrations of N and P along longitudinal transect during dry weather index period. Station numbers are begin at station 1 (proximal to ocean mouth) and terminate at Segment 2 site (Station 12; see Figure 1.1).

31 300 300 20 16 250 14 250 15 12 200 200 10 150 8 150 10

TP (uM)

TN TN (uM)

DIN (uM) DIN 100 6 SRP (uM) 100 4 5 50 50

Index Period 1 Period Index - Winter 2 0 0 0 0 300 300 20 16 250 14 250 15 200 12 200 10 150 8 150 10

TP (uM)

TN TN (uM)

DIN (uM) DIN 100 6 SRP (uM) 100 4 5

Index Period 2 Period Index - Spring 50 50 2 0 0 0 0 300 300 20 16 250 14 250 15 200 12 200 10 150 8 150 10

TP (uM)

TN TN (uM)

DIN (uM) DIN 100 6 SRP (uM) 100 4 5 50 50 2

Index Period 3 Period Index - Summer 0 0 0 0 300 300 20 16 250 14 250 15 200 12 200 10 150 8 150 10

TP (uM)

TN TN (uM)

DIN (uM) DIN 100 6 SRP (uM) 100 4 5 50 50 Index Period 4 Period Index - Fall 2 0 0 0 0 1 3 5 7 9 11 1 3 5 7 9 11 Transect # Transect # DIN SRP TN TP

Figure 2.7. Flood-tide concentrations of N and P along longitudinal transect during dry weather index period. Station numbers are begin at station 1 (proximal to ocean mouth) and terminate at Station 12 (Segment 2; see Figure 1.1).

32 500 100 140 4.5 Index 1 Index 2 Index 1 Index 2 120 4.0 400 80 100 3.5

300 60 80 3.0

M)  60 2.5

TN ( TN 200 40 40 2.0

Ammonia (mM) Ammonia 100 20 20 1.5 0 1.0 0 0 0.5 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 120 5 100 80 Index 3 Index 3 Index 4 Index 4 100 80 4 60 80 60 3 60

 40 2 40 40

TN ( TN

20 (mM) Ammonia 20 1 20 0 0 0

-20 0 22 24 26 28 30 32 34 36 38 30 31 32 33 34 22 24 26 28 30 32 34 36 38 30 31 32 33 34 Salinity (ppt) Salinity (ppt) Salinity Salinity

500 50 Index 1 Index 2 400 40 Figure 2.8. Mixing diagrams (concentration as a function of 300 30 M) salinity) of TN (top left), Ammonium (top right), and  200 20 Nitrate+Nitrate (bottom left) during each of the four index

N+N ( N+N 100 periods. All concentrations are given in μM. Red fill circles 10 0 indicate transect samples taken during the flood tide, while 0 white fill circles indicate those taken during ebb tide. A linear 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 trend indicates conservation behavior of the constituent with

50 8 salinity, while a concave shape represents production (a Index 3 Index 4 source) and a convex shape represents consumption (a sink) of 40 6 the constituent. 30

M) 4  20

N+N ( N+N 2 10 0 0 22 24 26 28 30 32 34 36 38 30 31 32 33 34 Salinity Salinity

33 10 6 Index 1 Index 2 8 4 6

 4

TP ( TP 2

2 0 0

0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 10 10 Index 3 Index 4 8 8

6 6

 4 4

TP ( TP

2 2

0 0

20 22 24 26 28 30 32 34 36 38 30 31 32 33 34 Salinity (ppt) Salinity (ppt) 5 6 Index 1 Index 2 4 4 3

M)  2 2

SRP( 1

0 0

-1 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35

10 10 Index 3 Index 4 8 8

6 6

 4 4

SRP ( SRP

2 2

0 0

20 22 24 26 28 30 32 34 36 38 30 31 32 33 34 Salinity (ppt) Salinity (ppt)

Figure 2.9. Mixing diagrams of TP (top) and SRP (bottom) concentration (μM) during each of the four index periods. Red fill circles indicate transect samples taken during the flood tide, while white fill circles indicate those taken during ebb tide. A linear trend indicates conservative mxing of the constituent with salinity, while a concave shape represents production (a source) and a convex shape represents consumption (a sink).

34 2.3.2 Seasonal Trends in Primary Producers This study assessed seasonal trends in biomass and or percent cover of three aquatic primary communities:  phytoplankton (measured as suspended chl a)

 macroalgae and cyanobacterial mats (biomass and percent cover)

 microphytobenthos (MPB; measured as benthic chl a) A fourth community, SAV, was not observed in the SMRE. Figure 2.10 shows the comparative biomass of phytoplankton, macroalgae and MPB, standardized to mass of carbon (C) per unit area by 2008 sampling period for Segments 1 and 2; Figure 2.11 shows interannual variation in carbon biomass between TMDL and Bight ‘08 studies. Biomass and cover between the two sampling years was similar (Table 2.5). Overall, carbon attributable to phytoplankton biomass was insignificant relative to macroalgal and MPB biomass. During the winter index period, no biomass or cover of macroalgae was observed. By the spring index period, MPB dominated the aquatic primary producers. A shift towards dominance by macroalgae and cyanobacterial mats occurred during summer and fall, with peak macroalgal biomass (238±88 g dry wt m-2 or 1465 ±548 g wet wt m-2) and percent cover (100%) at Segment 1 during the September 2008 index period and peak biomass (44 g dry wt m-2) at Segment 2 during July 2008 (Figure 2.12). This pattern was generally repeated during the 2008-2009 Bight ‘08 field survey (Figure 2.11, albeit with lower peak concentrations of macroalgae during the summer 2009 (94 g dry wt m-2).

Segment 1 Primary Producer Carbon Biomass Segment 2 Primary Producer Carbon Biomass

)

-2 60.000 20.000

Phytoplankton ) 50.000 Phytoplankton MPB -2 15.000 MPB 40.000 Macroalgae Macroalgae 30.000 10.000 20.000 5.000 10.000

0.005 0.008

0.004 APPBiomass of m (g wt C dry 0.000 0 0.000

Biomass of Primary Producers (g C m dry wt Jan 08 Mar 08 Jul 08 Sep 08 Jan 08 Mar 08 Jul 08 Sep 08 Index Period Index Period

Figure 2.10. Areal mass of carbon associated with three types of aquatic primary producers (APP) observed Segment 1 in SMRE: phytoplankton, microphytobentos (MPB), and macroalgae.

35 60.00

)

-2 50.00 Phytoplankton 40.00 MPB Macroalgae 30.00 20.00 10.00

0.12

0.08

0.04

Biomass of Primary Producers (g C dry wt m wt dry C (g Producers Primary of Biomass 0.00 0 Jan-08 Mar-08 Jul-08 Sept-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Oct-09

Index Period Figure 2.11. Comparison of areal mass of carbon associated with three types of primary producers observed at Segment 1 during TMDL and Bight „08 field studies (Jan 2008-October 2009). Note that microphytobenthos (MPB) were sampled at different elevations during the TMDL field studies (100 cm below MLLW) and Bight „08 study (30 cm above MLLW). Macroalgal biomass and phytoplankton biomass were sampled in using comparable methods.

Table 2.5. Comparison of wet macroalgal biomass and percent cover at Segment 1 during TMDL and Bight „08 studies.

Study Time Period Wet Macroalgal Biomass % Cover (Mean ± SD) (Mean ± SD) g m-2 TMDL Field Study Jan-08 0 0 Mar-08 0 0 Jul-08 196±181 82±17 Sept-08 1465±548 100±0 Bight 08 Study Nov-08 1310±1498 93±14 Jan-09 10±9 1±3 Mar-09 30±23 3±4 May-09 90±128 4±10 Jul-09 218±24 22±30 Oct-09 1714±118 33±23

36 A) Segment 1 Biomass B) Segment 2 Biomass

300 100

250 Macroalgae ) 80

)

-2 Cyanobacteria 200 -2 60 150

40 100

Biomass (g dry wt (gm dry Biomass 50 m wt dry (g Biomass 20

0 0 Jan 08 Mar 08 Jul 08 Sep 08 Jan 08 Mar 08 Jul 08 Sep 08 Index Period Index Period C) Segment 1 % Cover D) Segment 2 % Cover

100 100

80 80

60 60

40 40

20 20

0 0

% Cover of Macroalgal and Cyanobacteria Mats Cyanobacteria and Macroalgal of Cover % % Cover of Macroalgal and Cyanobacterial Mats Cyanobacterial and Macroalgal of Cover % Jan 08 Mar 08 Jul 08 Sep 08 Jan 08 Mar 08 Jul 08 Sep 08 Index Period Index Period

Figure 2.12. 2008 macroalgal and cyanobacterial mat biomass (top panels) and % cover (bottom panels) on intertidal flats for Segment 1 (A and C) and Segment 2 (B and D) by index period.

Microphytobenthos biomass appeared to be higher during the Bight ‘08 study (peak biomass of 3500 mg chl a m-2) than during the TMDL field study (peak biomass of 62 mg chl a m-2) , though sampling methods among the two studies were conducted at different water depths, making a true comparison difficult (Figure 2.13).

During the 2008 TMDL studies, phytoplankton biomass was highest during summer 2008, with mean values of 11.0 mg m-3 and 5.6 mg m-3 (Figure 2.14). During the Bight ‘08 study, phytoplankton biomass peaked in early spring (60 mg m-3), but remained fairly constant throughout the rest of the year. On average, Segment 1 showed slightly higher concentrations of chl a than Segment 2.

37 Segment 1 MPB Biomass Segment 2 MPB Biomass

120 140

) ) -2 100 -2 120 80 100

60 80 60 40 40 20

Benthic Chl a (mg Chla m Chla a (mg Chl Benthic m Chla a (mg Chl Benthic 20 0 0 Jan 08 Mar 08 Jul 08 Sep 08 Jan 08 Mar 08 Jul 08 Sep 08

Index Period Index Period

Figure 2.13. Segments 1 and 2 microphytobenthos (MPB; chl abiomass) by index period.

Segment 1 Water Column Concentration Segment 2 Water Column Concentration

)

-1

g L g 14



g L g 14 12  12 10 10 8 8 6 6 4 4 2 2 0

Suspended Chlorophyll a Conc. ( a Conc. Chlorophyll Suspended 0 Jan 08 Mar 08 Jul 08 Sep 08 ( a Conc. Chlorophyll Suspended Jan 08 Mar 08 Jul 08 Sep 08 Index Period Index Period

Figure 2.14. Segments 1 and 2 water column chlorophyll a concentrations by index period.

2.3.3 Seasonal Variation in Sediment Grain Size and Total Organic Carbon, Nitrogen and Phosphorus Characteristics by Index Period Large differences were observed in sediment grain size, total OC, and total nutrient between Segment 1 and 2 (Figure 2.15 and 2.16). Segment 1 generally had higher fractions of fine-grained sediments (mean of 43±22 with ranges of 20 to 55% fines at surface; 5 to 80% fines at depths from 4 to 10 cm). In contrast, Segment 2 sediments were coarse, with mean % fines of 5±8 with ranges of 1 to 30% fines at surface; 0.5 to 3% fines at depths from 4 to 10 cm). As a result, sediment %OC and sediment total nutrients also followed this general trend; Segment 1 sediment %OC, %TN, and %TP (means of 0.8 ±0.5, 0.10 ±0.07, and 0.05 ±0.07% respectively) was higher than that of Segment 2 (0.2 ±0.3, 0.007 ±0.03, and 0.02 ±0.01% respectively), particularly with respect to N content. Ninety-two percent of Segment 2

38 samples were non-detect for sediment N. Sedment %TP content was unusually high for some samples in Segment 2 (0.04 to 0.09 %TP, given the near zero sediment OC content and percent fines.

Vertically sediment TP content decreased consistently with depth for both Segment 1 and Segment 2 during all index periods, but this was not the case with % OC or %TN. From sampling period to sampling period, sediments at Segment 1 were much more variable in bulk characteristics than Segment 2 sediment. There were no consistent seasonal trends in bulk sediment characteristics over time in either Segment 1 or Segment 2.

3.0 0.30

2.5 0.25

2.0 0.20

1.5 0.15

1.0 0.10

Sediment % OC

Sediment % TN 0.5 0.05

0.0 0.00

0 20 40 60 80 100 0 20 40 60 80 100 0.10 % Fines % Fines 0.08

0.06 Segment 2 Segment 1 0.04

Sediment % TP

0.02

0.00 0 20 40 60 80 100 % Fines

Figure 2.15. Relationship between Sediment %OC, %TP and %TN as a function of grain size at Segment 1 (open circles) and Segment 2 (closed circles).

39 Segment 1 B. Santa Margarita Segment SiteSegment 1 2 Percent Fines Percent Fines 0 20 40 60 80 100 0 10 20 30 40 0 0

2 2

4 4 Percent Fines Percent Fines 6 C:N 6 C:N C:P 8 8 C:P

Depth (cm) Depth

Depth Depth (cm) 10 10

12 Nov 15, 2007 12 Nov 15, 2007 Percent Fines Percent Fines 14 14 0 20 40 60 80 100 0 10 20 30 40 0 0

2 2

4 4

6 6

8 8

Depth (cm) Depth

Depth Depth (cm)

10 10

12 Jan 21, 2008 Apr 2, 2008 12 Jan 21, 2008 Apr 2, 2008

14 14

0 0

2 2

4 4

6 6

8 8

Depth Depth (cm)

Depth (cm) Depth

10 10

12 Jul 22, 2008 Sep 30, 2008 12 Jul 22, 2008 Sep 30, 2008 C:N C:N C:N C:N 14 0 5 10 15 20 0 5 10 15 20 14 0 5 10 15 20 0 5 10 15 20

0 50 100 150 200 250 0 50 100 150 200 250 0 20 40 60 80 100 0 20 40 60 80 100 C:P C:P C:P C:P

Figure 2.16. Segment 1 and Segment 2 sediment grain size (as percent fines, ♦), carbon:nitrogen (C:N, ■), and carbon:phosphorus (C:P, ●) core ratios for November 16, 2007, and core ratiosfor each 2008 index period. Note difference in X- axis scale for Segment 1 and Segment 2 C:P and C:N core ratio by index period plots.

2.3.4 Seasonal Trends in Sediment Deposition Sediment deposition and removal events were measured using the particle tracer, 7Be. This cosmogenic 7 radionuclide is produced in the upper atmosphere by spallation of O2 and N atoms. Because Be is particle reactive, it will adsorb to any aerosols or dust present in the atmosphere at the time of formation. These particles are scrubbed from the atmosphere during rain events or fall out slowly as dry deposition. The 7Be particles can then act as particle tracer proxies for all internal sediment movement, and track the downstream flow of sediment in streams (Collis et al. 2006).

Total and residual inventories (top panels, Figure 2.17) and new inventories (bottom panels, Figure 2.17) are shown for both stations in the SMRE. Segment 2 was a sandy streambed and retained less 7Be signal, while the muds at Segment 1 show strong deposition and resuspension processes throughout the year. Despite the high sand content at Segment 2, deposition and resuspension were observed for most of the year.

Figure 2.17. Total and residual inventories of 7Be (top panels) and new 7Be inventories (bottom panels) are shown versus time from November 2007 thru September 2008 for Segments 1 and 2.

Benthic sediment transport (mass flux) was quantified as the total mass of sediment deposited or resuspended for a sampling period (top panels, Figure 2.18) and a daily deposition or resuspension rate (bottom panels, Figure 2.18) for both Segment 1 and 2. The mass flux total (top) represents the amount of sediment deposited or removed between sampling trips and indicates that Santa Margarita is primarily a depositional/resuspension environment for the entire monitoring period with little erosion of the sediment bed occuring. Though because mass fluxes are not correlated with any precipitation events, it is likely that the mass fluxes primarily represent resuspension of the sandy sediment bed. The daily mass flux is the total divided by the number of days between sampling trips and is essentially as average rate. It does not account for rapid event sediment deposition or resuspension.

Figure 2.18. Mass flux for Segments 1 and 2 in the Santa Margarita River Estuary.

2.4 Discussion 2.4.1 Summary of Findings This component of the study documented three major findings: 1. The SMRE seems to be exhibiting symptoms of eutrophication, as documented by high biomass and cover of macroalgae and episodes of low DO (indicators being considered by the State of California for eutrophication in estuaries), and high estuarine TN and TP concentrations. a. Biomass and percent cover of macroalgae were high with a mean averages of 1465 to 1714 g wet wt m-2 over the fall 2008 and 2009 TMDL and Bight ’08 field studies and cover up to 100%. No established framework exists to assess adverse effects from by macroalgae, though a recent review (Fong et al. 2011) found studies documenting adverse effects of macroalgae on benthic infauna as low as 700 g wet wt m-2 and with cover greater than 30 to 70% and application of a European macroalgae assessment framework indicates biomass and cover in SMRE is sufficient to be considered impacted by algal overgrowth (McLaughlin et al. 2012).

42 b. Dissolved oxygen concentrations were found to be below 5 mg L-1 about 19% of the wintertime and 23% of the summertime. c. Total nitrogen and total phosphorus concentrations are at or above Basin Plan objectives of TN and TP (1 mg L-1 and 0.1 mg L-1 respectively) for most sampling periods.

2. High dry season concentrations of dissolved inorganic nutrients indicate anthropogenically- enriched nutrient sources. During the summer and fall, little freshwater was delivered to the

estuary, yet estuarine ambient dry season SRP and NH4 were especially high in Segment 2 (16.1

±10.1 μM SRP and 29.8 ±19.3 μM NH4) and NO3 in Segment 1 (69.4 ±29.2). Mixing diagrams (plots of salinity relative to nutrient concentrations) of transect data indicate dry season sources

of NO3, phosphate (PO4) and NH4, not associated with direct freshwater input. Lateral inputs of groundwater or, at Segment 2, runoff from holding ponds, may be contributing a source of nutrients to the estuary that has not been quantified.

3. Sediments in the SMRE in general were dominated by sands, with extremely low content of OC and N. Segment 1 generally had higher fractions of fine-grained sediments while Segment 2 sediments were mostly sand with very low %OC and often or non-detectable %N. Fluvially- dominanted river mouth estuaries such as SMRE have an inherent capacity to scour fine-grained sediments, thus making them less susceptible to eutrophication because particulate sources of nutrients such as watershed sediments and decaying organic matter tend to be more quickly removed.

2.4.2 Significance of Macroalgae in the SMRE Opportunistic macroalgae are highly successful in nutrient–rich freshwater and estuarine systems. These algae typically have filamentous or sheet-like growth forms (e.g., Cladophora or Ulva spp.) that can accumulate in extensive, thick mats over the seagrass or sediment surface. Although macroalgae are a natural component of these systems, their proliferation due to nutrient enrichment reduces habitat quality in four ways: 1) increased respiration at night and large O2 demand from decomposing organic matter, 2) shading and out-competing SAV and MPB (Fong et al. 2011), 3) impacts on the density of benthic infauna, which are a principle food source for birds and fish, and 4) development of poor aesthetics and/or odor (Fong et al. 1998, Kamer et al. 2001, Kennison et al. 2003).

As nutrient availability increases, it has been well-documented in many parts of the world that blooms of green or red macroalgae become dominant in shallow subtidal and intertidal estuaries and lagoons, replacing seagrass or MPB (e.g., Sfriso et al. 1987, 1992; Raffaelli et al. 1989; Valiela et al. 1992, 1997; Geertz-Hansen et al. 1993; Peckol et al. 1994; Marcomini et al. 1995; Page et al. 1995; Hernández et al. 1997; Hauxwell et al. 1998; Kamer et al. 2001). Figure 2.19 shows that as N availability increases, macroalgae become increasing dominant, eventually outcompeting MPB. Under extreme nutrient availability and in particular with higher P availability, cynanobacterial mats appear (Fong et al. 2011).

Figure 2.19. Conceptual model of the relationships between N loading rate and the community composition of primary producers in unvegetated shallow subtidal and intertidal habitat in California estuaries.

In the SMRE, the relative biomass of benthic primary producers followed a seasonal trend typical of eutrophic-hypereutrophic coastal lagoons (Fong et al. 1993, 1998; Kamer et al. 2001). During the winter index period (January 2008), flushing and scouring during storm events act together with low temperatures and light levels to inhibit growth of macroalgae. Microphytobenthos biomass peaked during the winter and spring index periods, but were relatively low in biomass (70 to100 mg chl a m-2. By the summer index period, however, MPB appear to be out-competed by macroalgae Ulva for both Segment 1 and 2, and cyanobacteria mats appeared in Segment 1 in the fall. Biomass and percent cover of macroalgae were high with a mean averages of 1465 to 1714 g wet wt m-2 over the fall 2008 and 2009 TMDL and Bight ‘08 field studies and cover up to 100% (September–November 2008). This dominance and high standing biomass macroalgae and cyanobacteria during the summer and fall suggest that the SMRE is moderately disturbed with respect to nutrient over-enrichment (Fong et al. 1993).

While primary producer biomass and percent cover are useful for understanding the extent of eutrophication in estuaries, there is currently no established assessment framework to determine whether an estuary has become “adversely effected” by macroalgae. A recent review (Fong et al. 2011) found studies documenting adverse effects of macroalgae on benthic infauna found thresholds as low as 700 g wet wt m-2 (Bona 2006) and adverse effects with cover greater than 30 to 70% (Jones and Pinn 2006, Pihl et al. 1995). Ongoing studies being conducted by SCCWRP and UCLA will help to provide additional data which which to select macroalgal management endpoints for the estuary, if desired.

Macroalgal mats can rapidly deplete dissolved inorganic nutrients from the water column (Pedersen and Borum 1997, McGlathery et al. 2007). This depletion of nutrients increases the rate of benthic flux of nutrients from the sediments by creating a concentration gradient, thus diverting N loss from denitrification and providing a mechanism for N retention and recycling within the estuary (Krause- Jensen et al. 1999, Fong and Zedler 2000). In the SMRE, the peak in macroalgae productivity coincided

44 with the reduced freshwater flow and tidal exchange from a narrow ocean inlet. Increased residence time of water during this time period would result in greater residence time, enhancing availability of nutrients that can promote the productivity of macroalgal blooms.

The presence of macroalgae in estuarine environments can alter DO concentrations significantly on a diurnal scale. High rates of respiration from elevated biomass may reduce DO content of estuarine waters at night (e.g., Peckol and Rivers (1995)), while decomposition of accumulated organic matter may cause a large microbial O2 demand both day and night (Sfriso et al. 1987). Dissolved oxygen concentrations found to be below 5 mg for approximately 19% of the wintertime and 23% of the summertime, indicating that macroalgal biomass per se was not the driving factor in depressed DO concentrations; sediment O2 demand as well as flux of degraded organic matter may also play a role; observations of tidal height relative to DO show low O2events were associated with neap tide cycles, indicating that water residence time is likely a controlling factor. During neap tides, exchange with oxygen-rich ocean waters is at a minimum and sediment O2 demand and autotrophic and heterotrophic respiration will act to deplete surface waters of oxygen. Factors affecting DO flux are explored further in Section3.

2.4.3 Patterns in SMRE Surface Water and Porewater Nutrient Concentrations and Sediment Bulk Characteristics Ambient nutrient concentrations within an estuary are the integration of various pathways of sources, sinks and transformations, including both uptake and release (Valiela et al. 1992, 1997; Dalsgaard 2003; Bergamasco et al. 2003; Paerl 2009). The relative ratios of the different species can provide some insight into the dominant processes controlling nutrient availability within the estuary.

Surface water nutrient concentrations measured at the ME site and within the estuary show the surface waters to be enriched, with dry weather TN ( 57 to 971 μM) greater then wet weather concentrations (97 to 231 μM) and wet weather TP approximately equal to dry weather (4 to 11 μM). During winter index and wet weather periods, NO3+NO2and SRP comprised the largest fractions of TN and TP respectively, typical of surface waters enriched with anthropogenic sources of nutrients. During the summer and fall, little freshwater was delivered to the estuary, and NH4 and SRP dominated estuarine

TN and TP respectively. In particular, estuarine ambient dry season SRP and NH4 were especially high in

Segment 2 (16.1 ±10.1 μM SRP and 29.8 ±19.3 μM NH4) relative to the other San Diego Lagoons in this study (McLaughlin et al. 2010a,b, 2011).

Mixing diagrams (plots of salinity relative to nutrient concentrations) of surface water transect data were particularly instructive as to whether freshwater versus marine endmembers are the primary source of nutrients and to what extent within estuary sources (e.g. storm drains, groundwater, benthic flux, biological release) or sinks (benthic flux, denitrification, biological uptake) are visible (Day et al. 1989, Boyton et al. 2006, Sutula et al. 2006, REFS). Mixing diagrams show that for the SMRE, sources or production of NO3+NO2 and SRP appears in the 0 to5 ppt zone of the estuary during the winter and spring index periods, consistent with the concept that additional sources of these constituents may be entering the estuary near Segment 2, either as surface or groundwater inputs.

45 Nitrate+nitrite was consistently lower throughout the summer and fall index periods then in the winter and spring, with very low concentrations in the upper estuary and higher concentrations in near Segment 1 (mean concentrations ranging from 37.5 to 95.5 μM). Since freshwater input is low during this period, other sources of NO3 must be entering the estuary near Segment 2 (e.g. groundwater or storm drains). Other internal sources such as nitrification (Seitzinger 1988), which converts NH4 into

NO3, are possible, but estimates of nitrification are not available for southern California estuaries.

In contrast to NO3, dry season ambient NH4 concentration were higher near Segment 2 then 1. Mixing diagrams show a consistent non-freshwater source of NH4 to the estuary throughout all index periods.

Typical sources of NH4 sources could include, benthic flux or non-point source inputs such as agricultural runoff, groundwater, or storm drains (Valiela et al. 2006). In Famosa Slough, Loma Alta Slough, and San Elijo Lagoon, dry season concentrations of dissolved inorganic nutrients were typically non-detect, because external inputs were low and macroalgae were able to deplete sediment sources of nutrients

(McLaughlin et al. 2010a,b, McLaughlin et al. 2011). In the SMRE, summer and fall water column NH4 and NO3 were still relatively high, indicating that additional sources of dissolved organic nutrients to the estuary are present.

Sediment organic matter can be decomposed by microorganisms via a series of biogeochemical reactions which result in the release of mineral forms of nutrients to sediment porewaters (Berner 1966). The grain size and organic matter content of the sediment set the capacity of the sediment to produce porewaters of various concentrations, since low organic matter content, associated with sands and coarse substrates, generally have low %OC, %N and %P content (Sutula et al. 2002). Segment 1 generally had higher fractions of fine-grained sediments (20 to 80% fines) and higher %OC, %N and %P, while Segment 2 sediments were >90% sand with very low %OC and often or non-detectable %N. Fluvially-dominanted river mouth estuaries such as SMRE have an inherent capacity to scour fine- grained sediments, thus making them less susceptible to eutrophication because particulate sources of nutrients such as watershed sediments and decaying organic matter tend to be more quickly removed.

Sedment %TP content was unusually enriched for some samples in Segment 2 (0.04 to 0.09 %TP, given the near zero sediment OC content and percent fines. This suggests an anthrogenic source of P (Ruttenberg 2001, Sutula et al. 2002). Vertically sediment TP content decreased consistently with depth at both Segment 1 and 2 during all index periods, but this was not the case with % OC or %TN. As a result, porewater nutrients, DOC and TCO2 were 2 to 10 times higher in Segment 1 than in Segment 2 (see Section 3).

2.4.4 Significance Sediment Characteristics and Transport in the SMRE As noted above, sedimentary organic matter can serve as a source of remineralized N and P to porewaters and surface waters as the organic matter is decomposed. Sediment grain size typically decreased downcore associated with a decrease in N and P relative to organic C and an increase in porewater NH4 and PO4. However, the sediments were unlikely to provide a consistent source of remineralized nutrients to the porewaters and surface waters due to the constant resuspension of the sediment bed and large grainsize (Figures 2.16 and 2.18).

46 3 Estimates and Factors Influencing Benthic Oxygen, Carbon Dioxide and Nutrient Fluxes 3.1 Introduction Sediments are a potentially significant internal source of N and P to surface waters in estuarine systems. Watershed-derived sediments, deposited in estuaries during the wet season, carry an associated particulate N and P load (Sutula et al. 2004, 2006). When deposited in the estuary, particulate nutrients can be mineralized to biologically-available forms and may build up in high concentrations in sediment porewaters. These porewaters can diffuse into the overlying water column or be released through advective processes such as bioturbation by benthic infauna, forced flow of water through sediments by bioirrigation or tidal pumping, or physical resuspension of sediments through scouring or resuspension during strong tidal currents or storm flows (Boynton et al. 1980, Grenz et al. 2000, Jahnke et al. 2003). Once released to the water column, these particulate-derived nutrients are available for uptake by primary producers, including macroalgae, MPB, and SAV.

Primary producer abundance is often limited by availability of nutrients (Howarth 1988, Valiela et al. 1997, Kamer et al. 2004, Paerl 2009). Macroalgae generally obtain nutrients directly from the water column, though studies have shown that algae may intercept nutrients fluxing out of sediments (Lavery and McComb 1991, McGlathery et al. 2007). In Southern California, wet-season particulate-nutrient loads deposited in lagoons where shown to provide a significant source of nutrients that fueled excessive growth of SAV and macroalgae during the dry season (Boyle et al. 2004, Sutula et al. 2004, Sutula et al. 2006). Thus, sediment-derived nutrients may cause algal blooms to persist even when nutrient loading from the watershed is reduced to levels calculated to limit macroalgal biomass (Sutula et al. 2004, Neto et al. 2008).

The principal methods of estimating sediment contribution of nutrients (benthic flux) include benthic chambers (Hammond et al. 1985, Clavero et al. 2000, Berelson et al. 2003), sediment-core incubations (Risgaard-Petersen and Ottosen 2000, Welsh et al. 2000) and porewater profiles (Hammond et al. 1999, Qu et al. 2005). Vertical fluxes of solutes diffusing between the sediment and overlying waters can be calculated from Fick’s law of diffusion (i.e., porewater diffusive fluxes). The major physical controls on diffusive fluxes are sediment porosity and the diffusive boundary layer (DBL). However, diffusive fluxes generally underpredict true fluxes. Benthic chambers and sediment-core incubations are direct measurements and may integrate diffusive and advective transport of porewater by means of bioturbation/or bioirrigation processes (Berelson et al. 1999).

In addition to nutrients, the fluxes of O2,TCO2, and trace metals provide valuable information on the biogeochemical functioning of the sediments. In particular, O2 and TCO2 fluxes provide insight on the rates and dominant pathways of organic matter mineralization and benthic community metabolism, which are of primary interest in understanding ecosystem functioning and disturbances caused by eutrophication (Ferguson et al. 2003, Ferguson et al. 2004, Qu et al. 2005). The production of total inorganic C, measured as the release of TCO2 from the sediment to the overlying water, has been used to interpret the balance between aerobic and anaerobic mineralization since both yield carbon dioxide

47 (CO2) as the ultimate oxidation product of carbon (Berelson et al. 1998, Hammond et al. 1999). Measurement of dissolved Fe and Mn pore concentrations and fluxes provide valuable information about the redox chemistry of the benthic boundary layer, since these constituents are only released if the environment has a sufficiently low redox potential (hypoxic).

This component of SCCWRP studies had two objectives:

1) Measurement of porewater N, P, TCO2, sulfide, Fe and Mn concentrations to provide information about the sediment biogeochemistry and redox status of SMRE sediments.

2) Estimation of in situ flux of nutrients, DO, and TCO2 fluxes between sediments and surface waters. Benthic fluxes were estimated via direct in situ measurements of nutrient flux and

sediment O2 demand using benthic flux chambers. These data are compared to key factors (sediment characteristics and nutrient content, primary producer biomass as described in Section 2) known to control fluxes in order to understand key drivers on the magnitude and direction of flux.

3.2 Methods 3.2.1 Field Methods 3.2.1.1 Porewater Concentrations Sediment porewaters were sampled within Segment 1 and 2 using porewater equilibrators (peepers: (Hesslein 1976)) during each index period (Figure 3.1). When the peepers are placed into the sediment, solutes from the porewaters come into contact with the filter and a concentration gradient is established between the cell water (no solute) and the porewaters. This causes solutes to diffuse into the cells and, over time, equilibrium is established between the peeper cells and the porewaters whereby the concentrations on both sides of the filter paper are equal. Each peeper was constructed from a 50 x 18 cm solid plexiglass frame into which cells (0.5 x 3.0 x 13 cm) were milled in at a spacing of approximately 1 cm, which are used to sample a depth profile of the sediment porewaters. Each cell is filled with distilled, deionized water that had been bubbled with N gas for 24 hours to remove the O2 and covered with a 0.45 µm polycarbonate filter paper. The filter is held in place by an outer plexiglass frame secured with Teflon screws. Peepers are kept under a N atmosphere until deployment. Peepers were pushed by hand into the subtidal sediment, making sure that the peeper is vertical and the top of the sediment surface was flush with the top well of the peeper. Peepers were secured with a 30 m cable attached to a stake driven into the upper intertidal zone to facilitate recovery and the location was recorded using GPS coordinates. After a two-week equilibration period (Hesslein 1976, Brandl and Hanselmann 1991), the peepers were retrieved. Peeper recovery was coordinated with the collection of the sediment core and a collection of ambient bottom water (Section 2). Sediment cores for bulk characteristics and nutrients, described above, were collected within 2 feet of the peeper location. Immediately following retrieval, the peepers are placed inside large format ziploc bags that were purged with N gas to minimize artifacts from oxidation of porewater fluids. Porewater samples were extracted from each well using a repeater pipette, dispensed into vials and immediately frozen for analysis. Wells sampled represent porewater depths of: 0-1, 1-2, 2-3, 3-4, 4-5, 5-6, 7-8, 10-11, 13-14 cm. Each peeper

48 is processed within 15 minutes of recovery. Following sub-sampling of the peeper, ambient bottom water samples were also filtered, collected into vials and frozen for analysis. All water samples were analyzed for the following: sulfide, NH4, NO3, NO2, SRP, TDN, TDP, dissolved Fe, dissolved Mn, total carbon dioxide, and DOC. Before freezing sulfide samples were preserved with zinc acetate. One field blank was collected for each porewater analyte and a field blank and duplicate were collected for each ambient sample. Surface water samples were collected at the time of peeper retrieval.

Figure 3.1. Graphic depicting how porewater profiles are generated from porewater peepers.

3.2.1.2 Measurement of In Situ Benthic Fluxes

In situ sediment nutrient, trace metal, and DOC fluxes and sediment O2 demand were measured using benthic flux chambers (Burdige et al. 1999, Berelson et al. 2003, Elrod et al. 2004). A minimum of two replicate chamber deployments were conducted in each segment during each index period; each replicate was incubated for three to five hours. Water samples were periodically drawn from the chamber as O2 levels within the chamber decline, with time periods between chamber sampling events based on the rate of O2 decline in the chamber (Figure 3.2). These samples, when analyzed, yield the change in concentration of the targeted analyte over time. The surface area of the chamber is known and the volume of water contained with the chamber can be calculated, therefore, a flux rate can be derived.

49 Four identical benthic flux chambers were built based on a modified design from Webb and Eyre (Webb and Eyre 2004). The chamber is made of clear acrylic measuring 25 cm x 25 cm x 26 cm (l x w x h) mounted to an aluminum frame and is designed such that 10 cm of the chamber height is submerged in the sediment (leaving a height of 16 cm above the sediments) (Figures 3.3 and 3.4). The chamber frame is placed on top of an acrylic “skirt”, a thin sheet of acrylic measuring 24” x 36” with a hole cut in the center. This “skirt” allowed for the acrylic chamber to sink into the sediments but prevented the frame from also sinking into the sediments and thus changing the chamber height over the deployment time. When properly deployed the total chamber volume is 10 liters. Two of the chambers were left clear and open to variations in ambient light throughout the deployment (light chambers, Figure 3.5); the other two chambers were covered in aluminum foil to prevent ambient light from penetrating the chambers (dark chambers).

400 Light Chamber Dark Chamber 350 Ambient Water

300

250

200

Dissolved Oxygen (uM) Oxygen Dissolved 150

100 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00

Figure 3.2. Typical chamber time series of dissolved oxygen concentration within the light and dark chambers relative to ambient surface water (Segment 2, July 2008). Oxygen concentrations in both the light and dark chambers steadily decreased over the incubation. Flux calculations were made during the most linear part of the curve.

Figure 3.3. Schematic of benthic chamber design as viewed from above.

Figure 3.4. Schematic of benthic chamber design as viewed from side.

51 Sondes with Hand-held Display Ambient Sonde

Light Chamber Dark Chamber Light Chamber Dark Chamber

Figure 3.5. Flux chambers during deployment.

Each chamber is equipped with a YSI 6920 data sonde containing a temperature/conductivity probe, optical DO probe, and pH probe allowing for continuous measurements within each chamber and of ambient water every minute. All probes were calibrated in the laboratory before deployment. Two of the chamber probes were connected to a YSI 650 hand-held data display unit allowing for real-time monitoring of DO levels within each chamber. Such a set up allowed the field team to set the timing of chamber samplings to insure that all five samplings were evenly spaced in time and that no sampling would occur after the chamber DO levels fell below 2 mg L-1.

The chamber is “plumbed” with tubing from the chamber to a peristaltic pump which keeps water circulating through the chamber, preventing the development of a benthic boundary layer which would alter the benthic-flux rate (Webb and Eyre 2004). An additional tube is connected to a clean 60 ml syringe which is used to pull water samples from the chamber at the designated intervals. There were five sample draws from each chamber and each sample draw removed approximately 130 ml of water from the chamber (two syringes plus 10 ml of rinse). In order to maintain consistent chamber volume, water from a “make-up” bag is drawn into the chamber as the sample water is withdrawn. The two syringes used to draw chamber water at each sampling port are immediately taken to the shoreline for processing.

Sediments were mildly disturbed during deployment, so chambers were allowed to equilibrate with their surroundings before the tops were closed. Chambers were closed when the turbidity measurement in chamber 1 returned to baseline. Dissolved oxygen, temperature, salinity, turbidity, and pH were measured continuously in each chamber and the surface water directly adjacent to the chambers with data sondes. Dissolved oxygen concentrations in the chambers were monitored during the incubation and observed to steadily decline in both the light and dark chambers over the course of the experiment relative the ambient DO concentration (Figure 3.2). Samples were pulled from the chamber at evenly spaced intervals to measure the change in concentration within the chambers as a function of time; these data were used to calculate the flux from the sediments. The interval between samplings was determined based on the rate at which the real-time measurements of DO decreased; the aim of the experiments was to collect five distinct samplings before the DO levels fell below 2 mg L-1 (62 µM).

52 Chamber water and ambient surface water samples were analyzed for TDN, TDP, NH4, SRP, NO3, NO2,

DOC, Fe, Mn and TCO2. One unfiltered split was collected for TN and TP, and then the syringe was fitted with an MCE filter, which was rinsed with 10 ml of sample water, and splits were collected for dissolved nutrients (NO2, NO3, NH4, and SRP), and total dissolved nitrogen and phosphorus (TDN/TDP). The second syringe was fitted with a PES filter, which was rinsed with 10 ml of sample water, and splits collected for DOC, dissolved metals (Fe and Mn), and TCO2. All samples were placed in the dark on ice while in the field. Total carbon dioxide samples were analyzed in the laboratory within six hours of collection. The remaining samples were frozen upon return to the laboratory until analysis within their respective holding times.

After the deployment was completed, surface sediment samples were collected and analyzed for grain size, OC, organic N, and TP content, and sediment chl a. Algal biomass and SAV biomass were comprehensively harvested from the chamber whenever applicable, sorted, cleaned and weighed.

Ambient water samples were collected during both the benthic chamber deployment (surface waters) and the porewater peeper extraction (bottom waters). The protocol for sampling and processing was the same as given above for the transect sampling (Section 2.3.1).

3.2.1.3 Benthic Infauna Benthic infauna cores (5 cm diameter, 10 cm deep) were collected from each benthic flux chamber following deployment in each index period. Individuals were identified and counted by genus and extrapolated to estimate the number of infauna of each genus in the top 10 cm of each square meter of subtidal sediment.

3.2.2 Analytical Methods All water samples were assayed by flow injection analysis for dissolved inorganic nutrients using a

Lachat Instruments QuikChem 8000 autoanalyzer for the analysis of NH4, NO3, NO2, and SRP. Dissolved Fe and Mn were measured by atomic adsorption spectrophotometry on a Varian Instruments AA400. Water samples were assessed for TDN, TDP, TN and TP via two step process: first water samples undergo a persulfate digest to convert all N from all N compartments into NO3 and the P from all P compartments into orthophosphate; then the resulting digests are analyzed by automated colorimetry (Alpkem or Technicon) for nitrate-N and orthophosphate-P (Koroleff 1985). Water DOC was analyzed on a Shimadzu TOC-5000A Total Organic Carbon Analyzer with ASI-5000A Auto Sampler. Water TCO2 was analyzed on a UIC instruments carbon dioxide coulometer. Sulfide samples were allowed to react with N,N-dimethyl-p-phenylenediamine and ferric chloride under acidic conditions to yield the product methylene blue, and the concentration of methylene blue was determined spectrophotometrically at 668 nm. Concentration of sulfide in the sample was calculated by reference to a standard curve (absorbance vs. sulfide concentration). Inorganic nutrients and trace metals analyses were conducted by the Marine Science Institute at the University of California, Santa Barbara; TDN, TDP, TN, TP, and

DOC were run at the University of Georgia Analytical Chemistry Laboratory. Sulfide and TCO2 were measured by SCCWRP.

53 3.2.3 Data Analysis

Flux rates (F) for each constituent (dissolved nutrients, metals, TCO2, and O2) are calculated from the chamber height (h) and the change in constituent concentration within the chamber over time (dC/dt):

( ) Eq. 3.1

Concentration versus time was plotted as a linear gradient using all data that passed a quality assurance check. Use of the linear portion of the incubation curve assumes that the flux of a constituent is constant during the incubation interval (Figure 3.1).

Productivity at the sediment/water interface can be estimated from the fluxes of TCO2 and O2 as carbon fixation and gross primary productivity (GPP) respectively. Carbon fixation is a measure of the amount of inorganic carbon (carbon dioxide) converted to autotrophic biomass and is calculated from the difference between light (with photosynthesis) and dark (without photosynthesis) TCO2 fluxes:

Carbon Fixation = Flux TCO2light – Flux TCO2dark Eq. 3.2

Gross Primary Productivity is the rate at which primary producers capture and store chemical energy as biomass and can be calculated from the difference between light (with photosynthesis) and dark

(without photosynthesis) O2 fluxes:

GPP = Flux O2light – Flux O2dark Eq. 3.2

3.3 Results 3.3.1 Sediment Porewater Concentrations Differences were observed in porewater N and P concentrations among index periods and sites, as well as vertically (Figure 3.6). With respect to N, Segment 1 TDN mean concentration were roughly an order of magnitude higher than Segment 2. The mean TDN concentrations of the top 6 cm in Segment 1 ranged from 413 ±279 μM TDN during January 2008 to 1168 ±918 μM TDN in September 2008, while that of Segment 2 ranged from 49 ±8 μM TDN during March 2008 to 114 ±46 μM TDN in July 2008. The relative compositions of N forms (NH4, NO3+NO2, and dissolved organic nitrogen (DON)) likewise varied enormously between the two sites. In Segment 1 sediments, DON typically comprised 80% within the first 1-2 cm, then dropped off to <10%, while NH4 comprised >85% of TDN at depths >2 cm. Nitrate+nitrite typically had concentrations of 10 to 30 μM in the top 1. In Segment 2 sediments during the first two index periods, DON and NO3+NO2comprised approximately 40% each of TDN, while NH4 was <10%. During the summer and fall index periods, TDN increased and NH4 comprised 65 to 80%, with DON responsible for the remainder and nitrate+nitrate < 2%.

54 A) Segment 1

Index Period 1: January 21, 2008

SRP (uM) DOC (uM) Ammonium (uM) Manganese (uM) TCO2 (uM) 0 100 200 300 0 500 1000 1500 2000 0 800 1600 2400 3200 0 50 100 150 200 2500 1500 3000 4500 6000 0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14

Index Period 2: April 2, 2008

0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14

Index Period 3: July 22, 2008

0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14

Index Period 4: September 29, 2008

0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14 0 100 200 300 0 10 20 30 40 50 60 70 0 800 1600 2400 32000 100 200 300 400 500 0 2000 4000 6000 800010000 TDP (uM) Nitrate + NItrite (uM) TDN (uM) Iron (uM) Sulfide (uM)

55 B) Segment 2 Index Period 1: January 21, 2008

SRP (uM) DOC (uM) Ammonium (uM) Manganese (uM) TCO2 (uM) 0 25 50 75 0 250 500 750 1000 0 50 100 150 200 0 25 50 75 100 125 0 400 800 1200 1600 2000 0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14

Index Period 2: April 2, 2008

0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14

Index Period 3: July 22, 2008

0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14

Index Period 4: September 29, 2008

0 -2 -4 -6 -8

Depth (cm) Depth -10 -12 -14 0 25 50 75 0 10 20 30 40 0 50 100 150 200 0 20 40 60 0 20 40 60 80 100 TDP (uM) Nitrate + NItrite (uM) TDN (uM) Iron (uM) Sulfide (uM)

Figure 3.6. Results of sediment porewater sampling in the Santa Margarita River Estuary Segment 1 (A) and Segment 2 (B) during seasonal index periods; each row represents an index period, first column is total dissolved phosphorus (●) and soluble reactive phosphate (○), second column is nitrate+nitrite (▲) and dissolved organic carbon (■), third column is total dissolved nitrogen (■) and ammonium (□), fourth column is iron (■) and manganese (●), fifth column is sulfide (▲) and total carbon dioxide (●). The same scale applies to each column.

56 As with N, mean porewater TDP concentrations at Segment 1 were an order of magnitude higher during the winter and spring index periods and a factor of 5 higher than that of Segment 2 during summer and fall index periods. The mean TDP concentrations of the top 6 cm in Segment 1 ranged from 30 ±33 μM TDP during January 2008 to 95 ±82 TDN in the September 2008 index period, while that of Segment 2 ranged from 1 ±1 μM TDP during March 2008 to 27 ±12 μM TDP in July 2008. The relative compositions of P forms (SRP versus dissolved organic phosphorus (DOP) were consistent between the two sites. SRP generally comprised 70 to 90% of TDP at Segments 1 and 2 throughout all index periods.

Segment 1 and Segment 2 mean DOC concentrations generally were of the same order of magnitude and followed the same seasonal trend. Peak mean concentration occurred during the Spring index period, and were slightly higher at Segment 1 (1133 ±503 μM DOC) than at Segment 2 (665 ±241 μM DOC). During other time periods, mean concentrations were fairly comparable, with intermediate concentrations of 435 to 556 μM DOC during the January and July 2008 index periods and the lowest concentrations (129 to 176 μM DOC) during the September 2008 index period.

Mean TCO2 concentrations were higher three times higher in Segment 1 (2185 to 3571 μM) than in

Segment 2 (578 to 937 μM TCO2), with no strong seasonal trend. Segment 2 TCO2 concentrations tended to be uniform with depth, while Segment 1 TCO2 typically peaked at mid-core, then declined.

At both Segment 1 and Segment 2, mean sulfide concentrations were near non-detect during the winter and spring index periods <2 μM. During the summer and fall, concentrations at Segment 1 were substantially greater during the July and September index periods (92 ±56 μM to 3870 ±3862 μM) than at Segment 2 (24 ±33 μM to 33 ±33 μM).

At both Segment 1 and Segment 2, vertical profiles of SRP, NH4, and TCO2 concentrations tended to covary, showing peaks at mid-depths of the core and declines further down core. Dissolved Organic

Carbon and to a lesser extent NO3+NO2 tend to covary with reduced Mn and Fe.

3.3.2 Dissolved Oxygen and Carbon Dioxide Fluxes -2 -1 The sediments in Segment 1 showed a small net uptake of O2 (-93 mmol m d ) and release of TCO2 during the winter (19 mmol m-2 d-1), indicating that during this time period the sediments were heterotrophic (respiration exceeds primary production; Figure 3.7). From spring through fall, however, -2 -1 light and dark chamber fluxes were fairly well balanced or a net release of O2 (0 to +125 mmol O2 m d ) -2 -1 and uptake of TCO2 ( -4 to -20 mmol TCO2 m d ) was observed, indicating that the sediments in the latter portion of the year were autotrophic (primary production exceeds respiration). There was good correspondence bewteeen the DO and TCO2 data, showing similar trends between both data types (Tables 3.1 and 3.2).

In contrast, sediments of Segment 2 showed almost opposite trends. Net O2 fluxes were positive (indicating autotrophy) during the winter and spring index periods (+21 to +23 ±26 mmol m-2 d-1 respectively; Figure 3.8). During summer and fall, net O2 fluxes were into the sediment, indicating net -2 -1 heterotrophy (-1 to 61 mmol m d ). Ratios of TCO2:O2 were 0.7 to 0.8 during the winter and spring index period increasing to 1.3 to 1.8 during the summer and fall. Ratios greater than 1.3:1 indicate that more CO2 is being produced than can be respired by aerobic decomposition (net heterotrophic) while the rest of the year is autotrophic (Eyre and Ferguson 2002b, Eyre and McKee 2002).

The mean of DO fluxes from Segment 1 and Segment 2 shows a seasonal trend, with a tendency towards autotrophy in the first three index periods, and net heterotrophy in the September index period (Table 3.1). Unfortunately, the data quality of continuous DO measured via sonde in the water column during the 2008 TMDL studies were poor. However, data from Bight ‘08 continuous data (presented in Section 2) taken during the subsequent year show no strong trends in seasonal trends in DO and no prolonged periods of hypoxia, consistent with these sediment DO flux results.

Among all chamber incubations at Segments 1 and 2, DO flux was positively correlated with TCO2 flux (-0.76, p<0.001; Table 3.2). Of co-factors measured in benthic chambers, such as sediment C:N, C:P, grain size, benthic chl a, benthic infauna, only DO flux was negatively correlated with salinity and TCO2 flux was negatively correlated with pH (Table 3.2).

Table 3.1. Mean and standard deviation of Segment 1 and Segment 2 DO fluxes by index period.

Index Period Mean Std. Dev. Jan 2008 25.2 53.4 Mar 2008 25.6 59.4 July 2008 13.7 64.2 Sept 2008 -16.6 69.8

58 Table 3.2. Spearman‟s Rank Correlation among DO, TC02, nutrient fluxes and factors known to influence flux (Temperature – Temp, sediment C:N Ratio (CN), sediment C:P (CP), total infaunal abundance (Infauna), sediment % fines, benthic chl a within chambers (chl a)). No macroalgal biomass was present in chambers. Table gives correlation (r) and p-value for α=0.05). Bolded values are significant at p-value<0.05. Metric Statistics Infauna Chl a %Fine C P C:N pH Salinity Temp TCO2 DO NH4 TDN TDP NO3 SRP Total Corr. 1 0.05 -0.12 0.01 0.14 -0.51 -0.09 0.54 0.14 -0.20 0.48 0.20 0.49 -0.24 0.42 infauna p-value 0.79 0.52 0.94 0.43 0.01 0.66 0.00 0.46 0.30 0.01 0.26 0.00 0.19 0.02

Benthic Corr. 1.00 0.09 0.02 -0.47 -0.36 -0.17 -0.15 -0.05 0.04 -0.40 -0.04 -0.36 0.05 -0.01 Chla p-value 0.61 0.89 0.01 0.06 0.40 0.46 0.77 0.86 0.02 0.83 0.04 0.78 0.96

% Fines Corr. 1.00 0.63 0.32 0.16 0.80 0.29 0.05 -0.31 0.19 -0.01 0.13 0.00 -0.04 p-value 0.00 0.07 0.41 <.0001 0.13 0.80 0.11 0.30 0.95 0.47 0.99 0.84

C:P Ratio Corr. 1.00 0.43 0.08 0.71 0.21 -0.23 -0.08 0.32 0.07 0.37 -0.18 0.08 p-value 0.01 0.68 <.0001 0.28 0.21 0.68 0.07 0.71 0.04 0.33 0.68

C:N Ratio Corr. 1.00 0.21 0.48 0.45 -0.17 0.06 0.39 0.06 0.40 0.00 0.28 p-value 0.28 0.01 0.02 0.34 0.75 0.03 0.74 0.03 0.99 0.12

pH Corr. 1.00 0.14 -0.03 -0.36 0.28 0.01 0.10 -0.05 -0.10 -0.26 p-value 0.48 0.88 0.06 0.15 0.95 0.60 0.82 0.62 0.18

Salinity Corr. 1.00 0.49 0.08 -0.35 0.57 -0.02 0.31 0.14 0.07 p-value 0.01 0.69 0.07 0.00 0.91 0.11 0.49 0.73

Temp Corr. 1.00 -0.02 -0.08 0.52 -0.13 0.37 0.04 0.38 p-value 0.92 0.67 0.00 0.51 0.05 0.85 0.04

TCO2 Corr. 1.00 -0.76 0.25 0.17 0.05 0.04 -0.01 p-value <.0001 0.17 0.35 0.80 0.81 0.94

DO Corr. 1.00 -0.40 0.03 -0.02 0.12 0.16 p-value 0.03 0.86 0.90 0.55 0.43

NH4 Corr. 1.00 0.49 0.76 -0.22 0.42 p-value 0.00 <.0001 0.22 0.02

TDN Corr. 1.00 0.46 0.11 0.33 p-value 0.01 0.56 0.06

TDP Corr. 1.00 -0.37 0.60 p-value 0.04 0.00

NO3 Corr. 1.00 0.05 p-value 0.77

59 300 A)

200

) 100

-1

-2 0

-100

-200 Light C02 Flux TCO2 Flux (mmol m (mmol Flux TCO2 -300 Dark C02 Flux Net C02 Flux -400 C Fixation -500 Jan 08 Mar 08 Jul 08 Sep 08 B) 600 Index Period 500 Light 02 Flux 400 Dark 02 Flux Net 02 Flux ) 300

-1 GPP d 200

-2 100 0 -100

Flux (mmol m (mmol Flux

2 O -200 -300 -400 -500 Jan 08 Mar 08 Jul 08 Sep 08

Index Period

Figure 3.7. Segment 1 light, dark, and net (24-hr average of light and dark) TCO2 fluxes, and estimated C fixation by index period (A); andlight, dark, and net O2 fluxes, and Gross Primary Productivity (GPP) by index period (B). Error bars represent the standard deviation between replicates.

60 200

100

)

-1

d -2 0

-100

-200 Light C02 Flux TCO2 Flux (mmol m (mmol Flux TCO2 Dark C02 Flux Net C0 Flux -300 2 C Fixation

-400 Jan 08 Mar 08 Jul 08 Sep 08 150 Index Period

100

)

-1 50

-2

Flux (mmol m (mmol Flux

2 -50 Light 02 Flux

O Dark 02 Flux -100 Net 02 Flux GPP

-150 Jan 08 Mar 08 Jul 08 Sep 08

Index Period

Figure 3.8. Segment 2 light, dark, and net (24-hr average of light and dark) TCO2 fluxes, and estimated C fixation by index period (A); and light, dark, and net O2 fluxes, and Gross Primary Productivity (GPP) by index period (B). Error bars represent the standard deviation between replicates.

61 3.3.3 Nitrogen Fluxes

Net fluxes (mean of light and dark incubations) of N (NH4, NO3, and TDN) exhibited some clear patterns with respect to season and segment (Table 3.3, Figure 3.9). Net fluxes across light and dark chambers show Segment 1 was a consistent source of TDN and NH4 during the summer and fall index periods and a sink for N03 during all index periods. With the exception of the March 2008 sampling period, the -2 -1 magnitude of NH4 flux out (5.2-28.2 mmol m d ) was slightly higher but within the same order of magnitude as N03 flux in -2.3 to -26.3 mmol m-2 d-1). At Segment 2, some of the same general patterns in TDN and NH4 can be found in the summer and fall, but with much smaller mean fluxes (e.g. -0.2 to 0.9 -2 -1 -2 -1 mmol NH4 m d and -0.2 to -1.0 mmol N03 m d ) and higher variability among light and dark chambers. As with Segment 1, NO3 flux was negative (into the sediments) for all periods. No significant differences existed between light and dark incubations for TDN, NH4, or NO3 fluxes (p-value>0.04; Figure 3.9).

Table 3.3. Nitrogen net fluxes and standard deviations from light and dark chamber fluxes (n=4) by index period. All fluxes are in mmol m-2 d-1.

Index Period Segment TDN NH4 NO3 Jan-08 2 -0.9±0.4 -0.03±0.1 -0.6±0.4 Mar-08 0.2±1.0 0.01±0.001 -1.0±2.3 Jul-08 2.5±1.4 0.9±0.01 -0.2±0.01 Sep-08 0.5±1.3 -0.2±1.9 -0.3±0.2

Jan-08 1 -12.9±8.0 12.5±3.3 -26.3±6.2 Mar-08 -14.8±2.0 -0.3±0.04 -7.5±8.4 Jul-08 5.3±2.3 28.0±4.2 -25.7±9.1 Sep-08 2.3±0.7 5.2±1.6 -2.3±1.9

Of the co-factors measured in benthic chamber incubations, NH4 flux had significant positive correlations with total benthic infaunal abundance (0.48), sediment C:N ratio (0.39), salinity (0.57), temperature (0.52), and significant negatively correlation with benthic chl a (Table 3.2). Nitrate fluxes had no significant correlations.

62 3.3.4 Phosphorus Fluxes Net fluxes (mean of light and dark incubations) of TDP and SRP exhibited some clear patterns with respect to season and segment (Table 3.4, Figure 3.9). As with N, net fluxes across light and dark chambers show Segments 1 and 2 were a consistent source of SRP during the summer and fall index periods ( 0.4 to 1.5 mmol m-2 d-1) and a sink for SRP in March 2008 (-0.08 to -0.3 mmol m-2 d-1). TDP fluxes were net positive at both Segments 1 and 2 for the September and January index period and at during the July period for Segment 1 (0.4 to 4.0 mmol TDP m-2 d-1). No significant differences existed between light and dark incubations for TDP and SRP fluxes (p-value>0.05; Figure 3.9) and DOP fluxes were highly variable in direction and magnitude (+2.5 to -0.6 mmol m-2 d-1).

Table 3.4. Phosphorus net fluxes and standard deviations from light and dark chamber fluxes (n=4) by index period. All fluxes are in mmol m-2 d-1.

Index Period Segment TDP SRP Jan-08 2 1.1±0.2 -0.2±0.06 Mar-08 0.1±0.01 -0.08±0.05 Jul-08 -0.3±0.05 0.4±0.2 Sep-08 0.4±0.2 0.4±0.4 Jan-08 1 0.6±0.1 0.6±0.4 Mar-08 -0.8±0.5 -0.3±0.2 Jul-08 4.0±0.3 1.5±1.4 Sep-08 0.4±0.2 0.7±0.3

Of the co-factors measured in benthic chamber incubations, SRP flux had significant positive correlations with total benthic infaunal abundance (0.42) and temperature (0.38); Table 3.2). TDP fluxes were significantly correlated with these same parameters, but also positively correlated with sediment C:P and C:N ratio (0.37 to 0.40) and negatively correlated with benthic chl a (-0.36).

63 A. Santa Margarita Segment Site 1 A. Santa Margarita Segment Site 2 100 60 10 10

)

) 50 )

-1

75 -1 40

50 30 -2

-2 5 5 -2

-2 20 25 10 0 0 0 0 -10 -25 -20

-50 -30 m (mmol Flux

Flux (mmol m (mmol Flux

-5 -5 m (mmol Flux

Flux (mmol m (mmol Flux

NO3 3 -40 4 NO3 -75

NO NH NH4 -50

NH NH4 -100 -60 -10 -10 800 10 1600

)

) 40 )

-1 -1 TDN

-1 400 -1 1200

d 20 d DOC

-2

-2 -2 5 800 0 0 400 -20 -400 0 0 -40 -800 -400 -60 TDN -5 -800 -80 -1200

TDN m (mmol Flux DOC DOC Flux (mmol m (mmol Flux DOC -1200

TDN m (mmol Flux

DOC Flux (mmol m (mmol Flux DOC -100 -1600 -10 -1600 10 8 6 6

)

) SRP )

-1

-1 8 -1

d TDP 6 d

-2

-2 6 3 3 -2 4 4 0 0 2 2

0 0 -3 -3 SRP

SRP Flux (mmol m (mmol Flux SRP TDP m (mmol Flux

-2 m (mmol Flux SRP TDP TDP m (mmol Flux -2 -6 -6 2 2 3 3

) ) Fe

)

-1 -1 2 2

-1

Mn -1

1 1 d

-2 -2 1 1

-2 0 0 -2 0 0 -1 -1 -1 -1 -2 -2 -3 -3 -2 -2

Fe Flux (mmol m Fe(mmol Flux -6 Fe -6

Mn Flux (mmol m (mmol Flux Mn

Fe Flux (mmol m Fe(mmol Flux -9 -9 m (mmol Flux Mn -3 -3 Mn -12 -12 Jan 08 Mar 08 Jul 08 Sep 08 Jan 08 Jul 08 Sep 08 Mar 08

Figure 3.9. Segment 1 and Segment 2 benthic NH4, NO3, TDN, DOC, SRP, TDP, Mn, and Fe fluxes for dark (dark grey bands) and light (light grey bands) by index period. Error bars represent the standard deviation between replicate chambers.

64 3.3.5 Benthic Infaunal Abundance In Santa Margarita, the benthic infauna community appears to support a diverse group of benthic infauna (Figure 3.10). Abundances are typically low during the winter and spring and increase in the summer and fall. Abundances are also greater for Segment 2 than for Segment 1, where sediments were more sandy and had lower OC and lower TN.

1e+5 Segment Site 1

1e+4

)

-2

1e+3 Polychaetes Capitellids Oligochaetes AliveMoll 1e+2 Crustaceans 1e+5 Other Segment Site 2 Total infauna

1e+4

Benthic Infauna Abundance (number m 1e+3

1e+2

1e+1 1 2 3 4

Index Period

Figure 3.10. Benthic infauna abundance counts for Segment 1 and Segment 2. Functional groups are shown as different colored bars.

65 3.4 Discussion Estuaries, at the terminus of watersheds, are typically subject to eutrophication due to high inputs of anthropogenic nutrient loads and hydromodification. Primary production in estuaries estuaries can be fueled by either “new” nutrients entering the system from the watershed or from “recycled” nutrients from the remineralization of particulate and dissolved organic matter that is brought into the estuary during rain events and transported to the water column via benthic flux. Shallow coastal lagoons with natural or anthropogenic muting of the tidal regime are particularly susceptible, because restricted exchange increases the residence time of water and thus the amount of time nutrients are available for uptake by primary producers (Sundbäck and McGlathery 2005).

Overall, this component of the study documented two principal findings:

1. Averaging over season and segment, benthic flux appears to provides net source of NH4 (4.4 -2 -1 -2 -1 mmol m hr ) and SRP (0.3 mmol m hr ) to surface waters. Mean annual influx of NO3 into the sediment was high (-10 mmol m-2 hr-1). Measured rates of denitrification were 2 orders of magnitude lower than this rate (T. Kane, UCLA Dissertation) and thus can only partially explain

the fate of this influx of NO3 into the sediments. A more likely explanation is that some portion

of this NO3 is being reduced to NH4 through DNR and is cycling back up to surface waters as NH4. Dissimilatory nitrate reduction is a pathway that is favored under anoxic sediment conditions.

2. On average, estuary metabolism tends to tip from net autotrophic (net positive flux of O2 to

surface waters) in spring to net heterotrophic (net uptake of O2 by sediments) in the fall. These

rates of O2 uptake were moderate relative to other eutrophic estuaries (e.g., Ferguson et al.

2003, 2004; Eyre and Ferguson 2005). High net TCO2 effluxes are typically driven by respiration of accumulated dead or decaying biomass (organic matter accumulation) in the sediments rather than respiration of live biomass. While SMRE had among the highest peak biomass of macroalgae documented, this biomass does not appear to accumulate in SMRE sediments from season to season. Surficial sediments were primary sandy, had surface C:N values <10, indicative of algal carbon sources, but C:N values increased with depth, typically with non-detect with respect to N, indicating that organic matter is not accumulating with depth. In fluvially- dominated river mouth estuaries such as SMRE, this lack of interannual organic matter accumulation would make them less susceptible to eutrophication and is a factor responsible for

the lower sediment O2 demand, given the high abundances of algal biomass.

3.4.1 Significance of Rates of Benthic Oxygen and Total Carbon Dioxide Eutrophication is typically defined by excess organic matter that fuels the development of hypoxia (i.e. low surface water DO concentration) as the organic matter is respired (Diaz 2001). When the consumption of O2 exceeds the rate of resupply (decomposition of excessive amounts of organic matter exceeds diffusion/mixing of O2 to bottom waters), O2 concentrations can decline below the limit for survival and reproduction of organisms (Stanley and Nixon 1992, Borsuk et al. 2001, Diaz 2001). The consequence of this is often a cascade of effects including loss of habitat and biological diversity, development of foul odors and taste, and altered food webs (Sutula et al. 2007). Dissolved O2 levels

66 that fall below 5 mg L-1 can be a stressor to aquatic life, and levels below 1 to 2 mg L-1 for more than a few hours can be lethal to both fish and benthic invertebrates (USEPA 2000, 2003). The basin plan water quality objective for the SMRE states that DO shall be greater than or equal to 5 mg L-1. The Bight ‘08 Eutrophication Survey documented DO concentrations below 5 mg L-1 approximately 22% of the year with brief periods of hypoxia, driven by muted tidal hydrology during neap tides and, to some extent, reduced freshwater flow and tidal inlet restrictions during the summer and fall.

Shallow estuaries, such as the SMRE, can develop hypoxia typically through one of three main processes: 1) as episodic events driven by primary producer blooms (net autotrophy, where production greater than decomposition) and decomposition (net heterotrophy, where decomposition is greater than production; McGlathery et al. 2007), 2) chemical O2 demand driven by sediment heterotrophic bacteria or redox reactions, and/or 3) during density-driven stratification which develops during intermittent closure to tidal exchange when the estuaries “trap salt” and preclude diffusion and mixing of O2 to bottom waters (Largier et al. 1991). In Santa Margarita, the first two of these processes appear to contribute DO dynamics, with Segments 1 and 2 seasonally behaving in opposite fashions. Dissolved oxygen fluxes in Segment 1 show this region of the estuary to be mildly net heterotrophic during the winter index period, indicating that the lagoon at this time was decomposing more organic matter than producing it at the time of sampling (Eyre and Ferguson 2002a, 2002b). By summer, the continuous data show that small or positive DO fluxes, indicating that production is generally balancing respiration.

In contrast, net benthic O2 and TCO2 data suggest that the sediments of Segment 2 are net autotrophic during the winter and spring, moving toward to heterotrophic during the summer and fall. Despite high cover and biomass of macroalgae during the summer and fall, large diurnal swings are not evident Segment 2 continuous data and periodicity appears more related to tidal hydrology. Time series analysis is required to better separate the effects of primary productivity versus tidal hydrology on O2 signatures; this analysis is being conducted as a part of the Bight ’08 Eutrophication Assessment and will be reported elsewere (McLaughlin et al. 2012).

Interestingly, comparison of O2 and TCO2 fluxes with in situ measurements in other systems indicate that

SMRE fluxes are generally lower than those found in most eutrophic estuaries (Table 3.5). High net TCO2 fluxes are typically driven by respiration of accumulated dead or decaying biomass (organic matter accumulation) in the sediments rather than respiration of live biomass. While SMRE had among the highest peak biomass of macroalgae documented, this biomass does not appear to accumulate in SMRE sediments from season to season. Surficial sediments were primary sandy, had surface C:N values <10, indicative of algal carbon sources, but these values increased dramatically with depth and with often non-detect with respect to N, indicating that organic matter burial and accumulation is not occurring with depth. A similar pattern was documented in Loma Alta Slough. Thus SMRE and Loma Alta Slough appear to be more dominated by fluvial process that scour fine-grained sediments rather than deposit them. In fluvially-dominated river mouth estuaries such as SMRE, this lack of interannual organic matter accumulation would make them less susceptible to eutrophication (Schubel and Kennedy 1984, Paerl et al. 1998, Bate et al. 2004).

67 Table 3.5. Comparison of fluxes from the Santa Margarita River Estuary to other estuarine environments.

Site O2 TCO2 SRP NH4 NO3

Santa Margarita (this study) Segment 1 4.5±66.5 -4.2±14.7 0.5±1.3 8.5±11.2 -13.9±14.3 Segment 2 -6.5±33.1 -3.1±23.8 0.1±0.4 0.2±0.9 -6.4±10.4 Loma Alta Slough (this study) 46.0±63.8 -6.7±58.0 0.1±0.2 1.8±4.9 -0.6±2.9 San Elijo Lagoon (this study) Segment 1 -12.3±17.9 28.6±21.7 0.4±0.3 0.9±0.3 -8.1±8.5 Segment 2 -51.5±26.8 98.1±36.4 0.8±0.3 11.8±2.3 -4.4±2.8 Buena Vista Lagoon (this study) East Basin -4.6±28.5 13.4±14.8 -0.3±0.6 0.3±2.2 -5.9±13.0 Central Basin -145.02±48.0 50.9±26.0 0.9±2.4 2.0±18.0 -1.2±4.3 Famosa Slough (this study) -43.8±17.7 58.9±46.4 -0.2±0.2 1.0±1.4 -0.2±0.5 Shallow SE Australian Lagoons -50 to 0 10 to 100 -3.4 to 0.3 0 to -60 (Eyre and Ferguson 2002) Hog Island Bay (Tyler et al. -0.003 to -0.33 to + -0.12 to +0.009 2003) +0.012 0.42 Shallow NE Australian Lagoons -0.2±0.3 -0.4 ± 0.3 (Ferguson et al 2004) Newport Bay -43 ± 20 107 ± 81 0.36 ± 0.52 5.7 ± 2.7 -3.0 ± 5.3 (Sutula et al. 2006) Los Angeles Harbor -18.9 ± 6.3 39 ± 29 0.33 ± 0.40 3.9 ± 2.9 -0.19 ± 0.18 (Berelson unpublished) San Francisco Bay -30 ± 7 24 ± 8 0.10 ± 0.50 1.1 ± 0.1 -0.5 ± 0.6 (Hammond et al. 1985) Monterey Bay -9.1 ± 2.4 9.9 ± 2.7 0.11 ± 0.07 0.56 ± 0.24 -0.57 ± 0.48 (Berelson et al. 2003) Chesapeake Bay -49 0.8 10.2 -2.9 to 0.2 (Callender and Hammond 1982, Cowan and Boynton 1996) San Quentin Bay, Baja CA -23.4 ± 10.7 31 ± 22.9 0.114 ± 2.15 ± 1.39 (Ibarra-Obando et al. 2004) 0.140 Tomales Bay -9.37 ± 9.56 20.7 ± 24.4 0.24 ± 0.40 1.96 ± 2.39 -0.01 ± 0.17 (Dollar et al. 1991) Plum Island Sound -33 to -170 23 to 167 -0.25 to 1.5 4.8 to 21.2 (Hopkinson et al. 1999)

68 3.4.2 Seasonal Patterns of Nutrient Fluxes and Benthic Metabolism In shallow coastal lagoons such as the SMRE, trends in benthic metabolism and nutrient flux are typically regulated by temporal changes in the primary producer community as well as process of diagenesis and cycling within the sediments (Sundbäck and McGlathery 2005). Porewater nutrient concentrations are controlled by a variety of factors, including exchange via the sediments, denitrification, nitrification, dissimilatory NO3 reduction, decomposition and uptake by organisms (Figure 3.11). Exchange with the surface waters can be driven by diffusive or advective processes such as tidal pumping, groundwater input, etc. Thus interpretation of porewater profiles and in situ benthic fluxes can yield rich information about the redox status and dominant processes controlling nutrients cycling witin the sediments and the degree to which they provide a net source of nutrients to support primary producers in the surface waters.

Figure 3.11. Pathways for nutrient cycling and decomposition of organic matter in the sediments.

For estuaries with high inputs of NO3, the balance between denitrification and dissimilatory NO3 two processes are important for the efficiency of N cycling and eutrophication in an estuary. Denitrification is the microbially-mediated conversion of NO3 to N gas, a process that occurs in moderately reduced

(low O2) sediments and represents an important permanent loss of N from an estuary (Seitzinger 1988).

Dissimilatory nitrate reduction (DNR) is the microbially mediated conversion of NO3 to NH4, a process which occurs in anoxic sediments (An and Joye 2006) and by which N can be recycled to surface waters and available for biological uptake. Averaging over segments and seasons, mean benthic flux appears to -2 -1 provides net source of NH4 (4.4 mmol m hr ) to surface waters. Interestingly, the magnitude of these

NH4 fluxes are among the highest documented in the literature (Table 3.6), despite very low and often

69 non-detectable sediment % N content. This suggests that one source of this sediment NH4 flux is DNR. -2 -1 Mean influx of NO3 into the sediment was high (-10 mmol m hr ). Measured rates of denitrification in undisturbed cores were 2 orders of magnitude lower than this rate (7 to 10 μmol m-2 hr-1; Table 3.3), 5 to 25X lower than the range of published rates in eutrophic estuaries (50 to 250 μmol m-2 hr-1; Seitzinger

1988) and thus can only partially explain the fate of this influx of NO3 into the sediments. A more likely explanation is that majority of this NO3 is being reduced to NH4 through DNR and is cycling back up to surface waters as NH4. The porewater profiles provide additional evidence of DNR; with depth, NH4 increases, with a corresponding decrease in NO3, signaling the DNR may be a dominant process (An and Gardner 2002, Gardner et al. 2006, Porubsky et al. 2009). This may be a dominant process in sediments of Segment 1 and Segment 2 during the summer and fall. Peak NH4 values coincided with higher SRP values and often with peaks in sulfide concentrations up to 9000 µM, signaling that sediments in an anoxic state and thus would favor DNR over denitrification. Denitrification may be playing a large role during the winter and spring time when sediments are better flushed and oxygenated (Seitzinger 1988). Thus in the winter and spring, the SMRE is better able to assimilate external DIN inputs through denitrfication, but as the estuary becomes more eutrophic during summer and fall, the efficiency of N loss is greatly reduced.

Table 3.6. Denitrification Rates Measured in the Santa Margarita River Estuary Subtidal Sediments on intact cores. All rates in µmol m-2 hr-1 (T. Kane, UCLA Dissertation 2011).

Segment January 2008 March 2008 July 2008 August 2008 2 0.1 7.6 0 0.1 1 10.8 0 0 2.1

Averaging over index periods, sediments of the SMRE appear to be source of SRP (0.5 to 0.1 mmol SRP m-2 hr-1). During winter and spring, sediments are acting as a sink for SRP. Sediments in this area appear more oxic, thus trapping P in particulate form associated with iron- and aluminum-oxides (Roden and Edmonds 1997). During the summer and fall index periods, sediments appear to act as a source to surface waters. The consequences of sulfate reduction for P cycling and fluxes, as indicated by peak sulfide concentrations, is important. As sulfate is reduced, Fe(II) is converted to iron-sulfides (Roden and Edmonds 1997). Because iron-sulfides cannot bind SRP, SRP adsorbed to Fe(II) are released, producing high porewater concentrations and net effluxes to surface waters.

In the SMRE, sediment % fines, OC, N and P content were major factor driving differences in the magnitude and direction of benthic fluxes observed between Segments 1 and 2. Porewater concentrations were orders of magnitude higher at Segment 1 then at Segment 2. Porewater TN at

Segment 1 (413 to 1168 uM) was dominated by NH4 throughout all sampling periods, while Segment 2 sediment TDN porewaters (49 to 114 uM) were dominated by NO3+NO2 and DON during the first 2 sampling periods and by NH4 and DON during the last two, when NO3+NO2 was non-detect. With respect to in situ benthic fluxes, NH4, NO3 and SRP fluxes were typically 1 to 2 orders of magnitude lower at Segment 2 than Segment 1. Ultimately, the differences between these segments are driven by

70 hydrology. High percentages of sand content and the low concentrations of redox indicators (NO3, Mn, Fe, Sulfide, and SRP) during the winter and spring indicate that sediments at Segment 2 appear well flushed and irrigated, consistent dominant fluvial hydrology of this site (Figure 3.12). In comparison, down estuary of I-5, the estuary becomes more depositional, which would explain the higher organic matter and nutrient content of the bulk sediments and porewater and, ultimately, higher magnitude of nutrient fluxes.

Figure 3.12. Sediment porewater profiles reflect redox status of the sediment.

Patterns of benthic nutrient cycling shifted seasonally, as can be observed from data representing the four index periods. The winter index period was characterized by frequent storm events. Peak flows during storm events in the winter index period would be expected to provide a subsidy of nutrients and particle-or organic matter-bound nutrients as well as an environment dominated by physical mixing of the surface waters and sediments (Smith et al. 1996, Correll et al. 1999, Paerl 2006). As evidence of this, surface sediments at both segments during this period contained the highest %fines of any of the four index periods (11 to 32% fines) and %OC and % N at Segment 1 (1% OC and 0.5% N) was an order of magnitude higher than the other index periods. Higher net sediment O2 demand at Segment 2 is consistent with fresh input of labile organic matter. However, sediments were well flushed, as demonstrated by flat and near-nondetect profiles of SRP, NH4, and sulfide (Froelich et al. 1979) and thus sediment O2 demand was moderate. As a result, primary producer biomass was low and fluxes may have been controlled to a greater extent by advective processes (Sutula et al. 2004, Sutula et al. 2006).

Ammonium and SRP fluxes are low and generally not signicantly different from zero, while NO3 fluxes are large and negative (into the sediment), suggesting denitrification maye occurring. Interestingly, porewater NO3 concentrations were relatively high during the spring index period at Segment 1. Peaks were observed in the vertical profiles of NO3 and coincided with elevated Mn and Fe porewater

71 concentrations and low sulfide, TCO2, NH4 and SRP concentrations (Figure 3.6), suggesting that the shallow surface sediments were perched at higher redox levels (Roden and Edmonds 1997). It is likely that denitrification is occurring during this time.This concept is supported by independent measures of denitrification in SMRE sediments, which showed peak rates in the winter and spring (Table 4.3).

During the spring sampling period, O2 effluxes out of the sediment and TC02 influxes peak, indicating net autotrophy (Eyre and Ferguson 2002a, 2005). As with the winter index period, NH4, SRP, and NO3 fluxes are low and into the sediment and porewater profiles indicate that the sediments are well flushed. Microphytobenthos biomass, increasing from winter time lows, in combination with well irrigated sediments, maybe responsible for this net autotrophy. Microphytobenthos can act to decouple nutrient turnover in the sediments from the overlying water column by acting as a “filter” for nutrient efflux from the sediments, at times completely intercepting nutrient fluxes across the sediment-water interface (McGlathery et al. 2004, McGlathery et al. 2007). Low fluxes of DIN compared to other eutrophic systems (Table 3.5), coupled with peak net O2 efflux and TC02 influx, are an indication that this phenomenon may be occurring.

During the summer and fall index periods, macroalgae replaced MPB as the dominant primary producer. Macraolgae have been shown to control the biomass of other primary producer communities, including benthic microalgae. Macroalgae have been shown to control the biomass of other primary producer communities, including benthic microalgae, because of a competitive advantage in nutrient uptake rate

(Fong et al. 1993, Fong et al. 2003). While MPB has been shown to enhance the O2 penetration of sediments, macroalgal biomass is know to shallow the depth of sulfate reduction, resulting in high porewater concentrations near the surface (Tyler et al. 2003). Sulfide reached peak concentrations surficial sediments and porewater sulfide and SRP were at their peak. Previous studies have suggested that macroalgae can drive an increased efflux of dissolved inorganic nutrients from sediments by drawing down surface water concentration, thereby increasing the concentration gradient (Tyler et al. 2003, Sutula et al. 2006). As these nutrients are trapped as biomass, macroalgae become an effective mechanism to retain and recycle nutrients within an estuary, diverting loss from denitrification or tidal outflow. This concept is supported by low to non-detectable rates of denitrification in the SMRE during this index period. Both NO3 uptake associated with primary production (MPB or macroalgae) as well as

DNR may have limited denitrification through competition for NO3 (Rysgaard et al. 1995, An and Joye 2001, Dalsgaard 2003, McGlathery et al. 2007). Denitrification is thought to be an unimportant sink for

N in shallow coastal lagoons because primary producers typically outcompete bacteria for available NO3 (McGlathery et al. 2007).

72 4 Santa Margarita River Estuary Nitrogen and Phosphorus Budgets 4.1 Introduction Nutrient cycling is one of the critical functions of estuaries (Day et al. 1989). The net balance of nutrient sources, transformations and losses from the estuary dictate the biomass and community structure of primary producers and bacteria, which forms the foundation for the estuarine food webs and dictates the habitat quality for benthic and pelagic fauna. One means of evaluating the efficiency of nutrient cycling within an estuary is to estimate its N and P budgets (Sutula et al. 2001). Budgets are a useful method to assess the relative importance of allochthonous inputs (“new” nutrients) versus internal recycling (“recycled” nutrients) on primary productivity (Mitsch and Gosselink 1993) – the main symptom of eutrophication.

The purpose of this section is to estimate SMRE N and P sources, losses, and change in storage for those terms which are readily estimated. The estuarine hydrodynamic and water quality models will be used in the future to develop refined nutrient budgets for the SMRE. However, in the interim, coarse estimates of nutrient budgets can be derived. This information, in conjunction with data estimating the change in storage, can shed light on the efficiency of nutrient cycling, identify potential sources that are unaccounted for and inform potential management actions in the SMRE.

4.2 Methods Budgets are estimated by determining the sum of source and loss terms from an estuary during the time period of interest (Figure 4.1). The sum of the source and loss terms, plus the change in “storage” of nutrients within specific compartments within the estuary (e.g. sediments, surface water, primary producers), should be equal to zero (Equation 4.1). Table 4.1 gives a summary of all the possible nutrient source, loss, and change in storage terms for an estuary and which of these were measured in the SMRE.

Figure 4.1. Conceptual model for development of budget estimates.

Loadwatershed ± Loadocean ± Loadgroundwater + Atmospheric Deposition - Denitrification + N

fixation - Storagealgae - Storageplants - Storagefauna + Storagepart + Storagedissolv -  Eq. 4.1

Storagewater + Residual = 0

Table 4.1. Summary of nutrient budget terms: sources, losses and change in storage. Budget Term Nitrogen Phosphorus Sources Terrestrial Runoff (wet and dry weather) CDM CDM Groundwater efflux Unquantified Unquantified Atmospheric Deposition Literature values Literature values Tidal surface water inflow Unquantified Unquantified Benthic nitrogen fixation UCLA Study N/A Losses Tidal surface water outflow Unquantified Unquantified Grounwater influx Unquantified Unquantified Denitrification UCLA Study N/A Sediment burial LSU Change in Storage Benthic exchange of nutrients with surface waters SCCWRP SCCWRP Plant/algal uptake/ release Residual of Sum of Sources, Losses and Change in Storage Terms Sediment deposition/resuspension of particulate LSU LSU nutrients Faunal uptake and release Assumed negligible Assumed negligible

Nutrient sources to the SMRE include: terrestrial runoff (wet and dry weather from creeks and storm drains), groundwater efflux, atmospheric deposition, ocean water inflow, and N fixation (Table 4.1). Nutrient losses to include: groundwater recharge, ocean water outflow, sediment burial, and denitrification. Change in storage includes benthic exchange with surface waters, aquatic primary producer biomass, sediment mass accumulation or loss, and faunal uptake and release.

These terms were estimated from monitoring data or from literature values for the period of November 1, 2007 through October 31, 2008 (Table 4.1 and Appendix 2).

Terrestrial runoff was estimated from wet and dry weather runoff monitoring conducted by CDM, Inc. (2009). Benthic N fixation and denitrification were measured during each of the index periods at each segment site (personal communication, T. Kane, UCLA Department of Biological Sciences Doctoral Dissertation).

Atmospheric deposition rates were not estimated in this study and no local data were available. Atmospheric deposition rates are estimated from a National Atmospheric Deposition Program site in the -1 - San Bernadino Mountains during 2007. Dry deposition for NH4 and NO3 for this site was 2.6 kg ha year 1 while wet deposition was 1.5 kg ha-1 year-1. Fewer data are available for atmospheric deposition of P;

74 data from south Florida indicate total (wet+dry) P fluxes ranging from 0.1 to 0.4 kg ha-1 year-1, with an average of 0.3 kg ha-1 year-1 (Redfield 2000, Ahn and James 2001). Typically ratios of dry:wet P deposition are 3:1. These numbers were used to estimate annual atmospheric loads for the SMRE, but are acknowledged to be highly uncertain.

Sediment mass accumulation and loss was estimated from long-term annual deposition rates measured by Louisiana State University (see Section 2). However, while these terms are important to the overall mass balance of nutrients, they were not included in the calculation of the residual because of lack of certainty on the net sediment transport through the estuary and because particulate nutrients are less biologically active then dissolved forms. Benthic flux accounts for sediment exchange with the surface waters, and thus incorporates the short-term effects of particulate nutrient deposition.

Groundwater interactions and the change in storage associated with faunal and emergent vegetation contributions were not quantified. Tidal surface water inflow and outflow cannot be estimated through a spreadsheet exercise, but rather throught the development of a hydrodynamic model for the estuary. Thus, net exchange with the coastal ocean is included in the residual budget term. However, concentrations of nutrients in the ocean are very low, so as an approximation, we assumed that ocean inputs of nutrients to the estuary are negligible.

In order to construct coarse budgets, a number of assumptions were necessary. First, benthic nutrient flux, denitrification and N fixation rates were extrapolated for the quarter over which the index period represents and the area of habitat available in the estuary. As these rates are expressed in a per square meter basis, the rates were multiplied by the representative area of intertidal and subtidal habitat in each of segment. It was assumed that only the mudflat and subtidal habitat in the main channel is subject to tidal hydrology. The large expanse of salt panne habitat west of the I-5 is infrequently inundated and therefore excluded from calculations. For the purposes of estimating benthic flux, it was assumed that nutrient exchange with the emergent marsh habitat was negligible and that the 102,191 m2 of mudflat habitat was inundated ½ of the time, so the representative area of mudflat used was 51,096 m2. Likewise, estimates of primary producers that are expressed on an areal basis (MPB and macroalgae) were multiplied by the total area of mudflat (102,191 m2) and subtidal habitat (455,551 m2). Table 4.2 presents the literature and assumptions were used to convert primary producer biomass to N and P.

Table 4.2. Literature values for Chla:C and C:N:P ratios of primary producer communities and assumptions to convert biomass to areal estimates of N and P associated with biomass.

Community Stoichiometry Reference (C:N:P) Phytoplankton, assumed 1.5 m chl a: C Ratio of 30:1 (Cloern et al. 1995), Redfield Ratio (Redfield 1958, water depth C:N:P = 106:16:1 Anderson and Sarmiento 1994) Cyanobacteria mats 50% C by dry wt Study data C:N:P = 550:30:1 (Atkinson and Smith 1983) Macroalgae 22% C by dry wt Study data, C:N:P = 80:5:1 (Eyre and McKee 2002) Benthic microalgae chl a: C ratio of 30:1 (Sundbäck and McGlathery 2005) C:N:P = 90:15:1 (Eyre and McKee 2002)

75 4.3 Results and Discussion Coarse seasonal N and P budgets for the SMRE provide order of magnitude estimates of nutrients available for primary productivity and can be used interpret the importance of external loads versus internal biological recycling in supporting it.

Wet weather and total dry weather terrestrial inputs, as measured at the ME site, were equal in magnitude (Table 4.3). Most of the dry weather input was concentrated during the Winter (Nov-Jan, 41,627 kg TN), representing 36% of the total annual export. Terrestrial inputs during summer and fall were low (535 to 0 kg TN respectively).

With respect to relative sources, terrestrial TN input overwhelmed all other sources2 during the wet season, but during the summer and fall estimated terrestrial input only represented 0-25% of TN loads to the surface waters (Table 4.4). In contrast, benthic flux ranged acted as a sink for about 10% of the terrestrial N during the winter index period but then became a dominant source during the summer and fall (79% to 97% of TN sources), the periods of peak primary producer biomass. Direct atmospheric deposition and benthic N fixation are negligible sources. Denitrification rates measured on undisturbed cores were low (see Table 4.3; T. Kane, UCLA Doctoral Dissertation 2011). However, rates were higher on slurried cores during the spring (mean of 114 µmol m-2 hr-1; T. Kane, UCLA Doctoral Dissertation 2011). This rate would produce loss from denitrification on the order ~ 1000 kg N, a term on the same order of magnitude as NO3 fluxes during this period.

Table 4.3. Comparison of estimated nitrogen source, loss and change in storage terms in the SMRE during dry weather periods (kg N). Positive and negative under “source and loss” terms indicates source and loss to the SMRE respectively. Positive and negative numbers in change of storage terms indicate gain and loss from compartment respectively. Residual is the sum of source and loss terms, minus the change in storage.

Dry Weather Dry Weather Dry Weather Dry Weather Annual (Wet Budget Term Wet Weather Nov-Jan Feb-Apr May-Jul Aug-Oct +Dry)

Source and Loss Terms Terrestrial runoff 39,278 30,255 10,837 535 0 80,905 N - Fixation -- 189 27 50 45 311 Atmos. Deposition 68 30 30 30 30 187 Denitrification -- -68 -47 0 -14 -128 Source + Loss Terms 39,346 30,406 10,847 614 61 81,274 Change in Storage Benthic N Flux -- -3,210 -3,475 1,702 617 -4,366 10 Producer N -- 0.1 1 484 1,114 1,600

Residual 39,346 27,196 7,370 1,832 -436 75,308

2 The net exchange of groundwater is unknown.

76 Table 4.4. Comparison of loads from watershed versus benthic nutrient flux (kg).

Annual Index Period 1 Index Period 2 Index Period 3 Index Period 4 (Wet+ Dry) Wet kg Weather Water- Benthic Water- Benthic Water- Benthic Water- Benthic Water- Benthic shed Flux shed Flux shed Flux shed Flux shed Flux

TN 39,278 30,255 -- 10,837 535 0 80,905 --

TDN 0 0 -3210 0 -3475 0 1702 0 617 0 -4,366

NH4 5,143 303 4250 841 -96 13 9705 0 1724 6,300 15,583

NO3 26,581 26,163 -8981 7,051 -2721 7 -8807 0 -837 59,801 -21,346

TP 5,255 1,279 -- 1,274 -- 328 -- 0 -- 8,137 --

TDP 3,425 1,055 189 1,153 -166 214 918 0 169 5,847 1,109

SRP 1,642 1,054 147 716 -29 157 666 0 140 3,569 923

A closer inspection of the balance between NO3, NH4 and TDN fluxes during each of the index periods is helpful in understanding the relative importance of two pathways of N cycling: denitrification and DNR

(Table 4.4). Denitrification is the microbially-mediated conversion of NO3 to N gas, a process that occurs is moderately reduced (low O2) sediments and represents an important permanent loss of N from an estuary (Seitzinger 1988). Dissimilatory nitrate reduction is the microbially mediated conversion of NO3 to NH4, a process which occurs in anoxic sediments (An and Joye 2006) and by which N can be recycled to surface waters and available for biological uptake. During the winter and early spring index periods, sediments appeared to be a net sink for TDN (~ 6685 kg TDN over 6 months), driven by large NO3 fluxes into the sediment (-11,702 kg TN over 6 months). During the Nov-Jan index period, these NO3 fluxes were counteracted by a flux of NH4 out of the sediments, while in the Feb-Apr index period NH4 fluxes were negligible. During the 6-month summer and fall index period, TDN fluxes out of the sediment (~

2319 kg TN) are driven by NH4 fluxes (11,428 kg TN), which are greater than NO3 fluxes into the sediments (-9,644 kg TN). The patterns illustrate that denitrification may be playing a large role during the winter and spring time when sediments are better flushed and oxygenated (Seitzinger 1988). Dissimilatory nitrate reduction is clearly a dominant pathway during the summer time and is likely responsible for the large NH4 fluxes observed during these periods. Thus in the winter and spring, the SMRE is better able to assimilate external DIN inputs through denitrfication, but is overwhelmed during summer and fall.

This budget shows that during peak periods of macroalgal blooms, benthic flux of NH4 is 1.5 to 19X the N required to grow the abundance of macroalgae observed (9705 and 1704 kg NH4 vs 484 and 1114 kg algal N for summer and fall respectively). Macroalgae is an efficient trap for DIN and has been shown to intercept benthic nutrient effluxes and can even increase the net flux by increasing the concentration gradient between sediments and surface waters (Tyler et al. 2001, 2003; Sutula et al. 2006). The storage of large quantities of N as algal biomass thus diverts N loss from denitrification and providing a mechanism for N retention and recycling within the estuary (Krause-Jensen et al. 1999, Fong and Zedler 2000). Denitrification is thought to be an unimportant sink for N in eutrophic, shallow coastal lagoons because primary producers typically outcompete bacteria for available N, and partitioning of NO3

77 reduction will shift to DNR to NH4 in later stages of eutrophication (Risgaard-Petersen and Ottosen 2000, An and Gardner 2002, Dalsgaard 2003, McGlathery et al. 2007).

Two types of data suggest an external source of DIN to the estuary not accounted for in the estimate of terrestrial loads from the ME site. First, mixing diagrams of NO3 suggest a source NO3 in the 1 to 5 ppt range in the mixing diagrams during the Nov-Jan index period. This coincides with proximity to agricultural fields which may be running off into the lagoon near this location and may be responsible for the observed trends. Second, comparison of mass emission sources of NO3 versus benthic influxes of

NO3 during the summer and fall show that SMRE surface waters has more NO3 than can be predicted by inputs from the ME site. These data indicate that there are additional sources, such as lateral groundwater inputs of NO3. This is a reasonable assumption, given the proximity of intensive, irrigated agriculture that was occurring at the time of sampling and permeable, sandy substrates which dominate the estuary.

Wet weather terrestrial runoff of TP constituted the majority (65%) of annual terrestrial input from the ME site (Table 4.5). Eighty-eight percent of the total annual dry weather runoff (2,882 kg) occurred over the winter and spring index periods. Terrestrial TP loads during summer and fall were low (328 to 0 kg TP, respectively). Wet weather terrestrial TP runoff was mostly 52% particulate P, while dry weather terrestrial loads ranged from 62 to 99% SRP (Table 4.4).

Table 4.5. Comparison of estimated phosphorus source and loss terms in the SMRE during dry weather periods (kg P). Positive and negative under “source and loss” terms indicates source and loss to the SMRE respectively. Positive and negative numbers in change of storage terms indicate gain and loss from compartment respectively. Residual is the sum of source and loss terms, minus the change in storage.

Annual (Dry Dry Weather Dry Weather Dry Weather Dry Weather P Budget Term Wet Weather Weather Nov-Jan Feb-Apr May-Jul Aug-Oct Only) Source and Loss Terms Terrestrial runoff 5,255 1,279 1,274 328 0 8137 Atmos. Deposition 3 3 3 3 3 14 Source + Loss Terms 5,259 1,282 1,276 331 3 8150 Change in Storage Benthic N Flux -- 189 -166 918 169 1109 10 Producer P -- 0.0 0.6 215 975 1145 Residual 5,259 1,470 1,110 1,034 -803 8,115

With respect to relative sources, terrestrial TP input overwhelmed all other sources3 during the wet season, but during the summer and fall estimated terrestrial loads only represented 0 to 32% of TP loads to the surface waters (Table 4.4). In contrast, benthic flux acted as a sink for about 10% of the terrestrial P during the spring index period but then became a dominant source during the summer and fall (75 to 97% of TP sources), the periods of peak primary producer biomass. Direct atmospheric deposition is a negligible source.

3 The net exchange of groundwater is unknown.

78 The P budget shows that during peak periods of macroalgal blooms, benthic flux of TP is 17 to 400% the P required to grow the abundance of macroalgae observed (917 kg TDP and 169 kg TDP vs 215 kg and

275 kg of algal P for summer and fall, respectively). As with N, macroalgae is an efficient trap for PO4 and has been shown to intercept benthic nutrient effluxes and can even increase the net flux by increasing the concentration gradient between sediments and surface waters (Tyler et al. 2001, 2003;

Sutula et al. 2006). Macroalgae can change redox condition directly under the mat, causing PO4 to solublize and become a source to surface waters (Roden and Edmonds 1997).

As with N, two types of data suggest an external source of PO4 to the estuary not accounted for in the estimate of terrestrial loads from the ME site. First, mixing diagrams of NO3 suggest show a source of

PO4 during all sampling periods. Second, the quantity of P required to grow macroalgae during the fall sampling period (975 kg TP) is not met by measured sources of terrestrial loads ( 0 kg TP) nor benthic flux (169 kg TDP). These data indicate that there are additional sources, such as lateral groundwater inputs of PO4, that are occuring.

Interestingly, both N and P appear to be seasonally limiting in the SMRE. Surface water nutrients were P limited during the winter, and N limited during the summer and fall (Figure 4.2). Thus management of both N and P sources and the ratios available for primary productivity is critical for managing eutrophication.

Figure 4.2. Ambient soluble reactive phosphorus versus dissolved inorganic nitrogen (nitrate, nitrite, and ammonium) from transect data taken in the northern channel (transect station # 11-15) and the southern basin (transect station # 1-10). The solid black line indicates the N and P requirements for both phytoplankton and benthic microalgae (N:P = 16:1), and the dotted black line indicates the N:P ratio for macroalgae and seagrasses (N:P = 30:1). If ambient values fall above these lines the communities are N limited. If values fall below, the communities are P limited.

79 4.4 Management Options to Reduce Eutrophication The SMRE has the advantage, as a river mouth estuary, that sediments do not appear to have accumulated excessive organic matter with depth. Hypoxia was present in the estuary, but not chronic. Therefore, options for management of eutrophication in the SMRE are aimed at reducing the availability of nutrients for primary production during the growing season and increasing tidal exchange in order to increase availability of DO and enhance denitrfication. Three types of options could be considered: 1. Reduce terrestrial loads in order to limit primary productivity. Emphasis should be placed on reducing both P as well as N from the watershed. Because sources during the growing season appear to be lateral inputs rather than those estimated by the ME site, minimizing these loads will be a critical and effective management strategy. 2. Increase flushing during peak periods of primary productivity, particularly when SMRE has reduced tidal exchange to surface water exchange with ocean during summer. Clearly this is a trade off with the need preserve available tidewater goby habitat during summer. Improved circulation during closed condition could help to limit stratification and therefore ameliorate, to a minor extent, problems with hypoxia. 3. Restoration to improve exchange with expansive area of wetland habitat west of I-5. Denitrification rates are typically highest in wetland habitats (Day et al. 1989). Restoration to increase connectivity and exchange of surface waters with the large expanse of intertidal habitat

south of the main channel would help to divert excessive NO3 available during dry season from DNR towards denitrification and permanent loss. This could be accomplished through grading of portions of the natural levee with separates this the central channel from the wetland area.

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87 Appendix 1 - Quality Assurance Documentation This section presents the results of the QA/QC procedures conducted throughout the sampling period at the SMRE.

Sampling Equipment Maintenance

Benthic chambers, porewater peepers and sediment cores were inspected prior to each deployment for cracks and/or deformities. Chambers were “re-plumbed” with new tubing and make-up bags during each index period and the diffuser bars were scrubbed internally and flushed with distilled water to make sure they were not clogged with sediment. Dark chambers were further inspected to make sure they were completely covered and no light was transmitted to the chamber. Peepers were cleaned and scrubbed with ethyl alcohol (to kill algae and microbial growth), rinsed in a 5% hydrochloric acid bath, then rinsed three times with distilled water prior to assembly to minimize contamination.

Data Sondes: Calibration, Drift, and Logging

Data sondes deployed in each benthic chamber and in the ambient surface water were calibrated not more than four days prior to deployment and a drift check was completed after deployment. No calibration problems or drift were apparent in any of the sonde maintenance events. During index period 1 sondes in chambers 3 and 4 failed to log data and during index period 3 the sonde in chamber 1 failed to log data. Reason for the lost data was due to a failure of the power supply.

Holding Times Violations

All water and sediment samples met the required holding times for benthic flux study in the SMRE SCCWRP special studies. Porewater samples had holding times violations for dissolved inorganic nutrients (NH4, NO3, NO2, and SRP) by UCSB for two periods: samples collected on 4/3/08 were not analyzed until 5/5/08 and exceeded the holding times by four days, and samples collected on 7/23/08 were run on 8/27/08 and exceeded the holding time by six days. These were considered minor violations and the data were used in calculations.

Laboratory Blanks

All of the laboratory blanks were reported to be below the level of detection, suggesting no bias from analytical techniques.

Field Blanks

One field blank was collected for each analyte during each benthic flux study and during each porewater peeper study. Field blank samples were collected using the same sample handling and collection equipment as field samples, except distilled- deinonized water was processed instead of sample water to assess possible contamination issues. Field blanks for total dissolved nitrogen, ammonium, total carbon dioxide and iron had a small percentage of samples fall outside the acceptable range. All other field blanks were below the minimum detection limit.

88 Laboratory Control Standards

All of the laboratory control standards were met acceptance criteria for percent recovery.

Laboratory Duplicates

Laboratory duplicates were processed by all analytical laboratories. A subset of samples (~5%) were randomly selected by the technician, split in the laboratory, and run separately to assess the comparability of the sample analysis process. All laboratory duplicates were within the analytical reporting limits for each analyte.

Field Duplicates

One field duplicate was collected for each analyte during each benthic flux study and during each porewater peeper study. Ammonium, NO3+NO2, and TDP had a small percentage of samples fail to meet the acceptance criteria. Field duplicates for all other analytes fell within the acceptance criteria.

Laboratory Matrix Spikes

Matrix spike samples were processed in the laboratory by adding a known concentration of a specific analyte to a field sample. The sample was analyzed prior to addition of the spike and again after addition. The calculated analyte concentration was prepared and compared to the analytical concentration. Matrix spike results are acceptable when the percent recovery is between 80 and 120%. All of the matrix spike results were within the acceptable range for the the SMRE special studies.

Table A1.1 QA/QC analysis for the SMRE Data Set. Constituent Lab Blanks Field Blanks Lab Duplicates> Field Duplicates Holding Time >MDL >MDL 25% RPD >25% RPD Violation Water Analyses TN 0% 0% 0% 0% 0% TDN 0% 12% 0% 0% 0% NH4 0% 12% 0% 12% 15%

NO3 + NO3 0% 0% 0% 12% 15% NO3 0% 0% 0% 0% 15%

TP 0% 0% 0% 0% 0% TDP 0% 0% 0% 12% 0% SRP 0% 0% 0% 0% 15% TCO2 0% 12% 0% 0% 0% Fe 0% 12% 0% 0% 0% Mn 0% 0% 0% 0% 0% S-2 0% 0% 0% 0% 0% Suspended chl 0% 0% 0% 0% a Sediment Analyses %OC 0% NA 0% 0% 0% %TN 0% NA 0% 0% 0% %TP 0% NA 0% 0% 0% Grain Size NA NA NA 0% 0% Benthic chl a 0% NA 0% 0%

89 Appendix 2 - Summary of Data to Support Modeling Studies This appendix provides SCCWRP data in tabular format to facilitate use of the data for the development and calibration of the water quality model for the SMRE.

Mass Emissions Table A2.1. Summary of mass emission site data by analyte for each storm event. CHLa NO3+ NH4 CBOD NO2 SRP TDN TDP TN TP TSS Storm Date (mg/ NO2 (mg/L) (mg/L) 3 (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) (mg/L) m ) (mg/L) 5-Jan- 1 0.0124 1.01 43.6 1.18 0.01 0.09 7.83 0.12 2.13 0.2 74.4 08 27-Jan- 2 0.6824 ND 21.2 1.27 0.03 0.13 2.77 0.23 2.24 0.32 255 08 26-Nov- 3 0.0046 ND 1.2 0.33 0 0.11 0.5 0.17 0.44 0.17 -0.2 08

Table A2.2. Summary of mass emissions data by analyte for each index period. Analyte Index Period 1 Index Period 2 Index Period 3 Index Period 4 Winter Spring Summer Fall (mg/L) Nov-Jan Feb-Apr May-July Aug-Oct Mean Stdev Mean Stdev Mean Stdev Mean Stdev TSS 13.3909 ± 9.6410 9.0000 ± 4.2426 0.2500 ± ± TN 3.1332 ± 0.6086 1.1215 ± 0.1608 0.3247 ± 0.0586 ± TDN NH4 0.0314 ± 0.0295 0.0871 ± 0.1509 0.0077 ± 0.0044 ± NO3 + 2.7202 ± 0.6786 0.7391 ± 0.0467 0.0081 ± 0.0007 ± NO2 NO2 0.0108 ± 0.0013 0.0095 ± 0.0015 0.0039 ± 0.0007 ± TP 0.1325 ± 0.0369 0.1318 ± 0.0175 0.1994 ± 0.0315 ± TDP 0.1093 ± 0.0443 0.1193 ± 0.0098 0.1299 ± 0.0391 ± SRP 0.1092 ± 0.0341 0.0741 ± 0.0327 0.0952 ± 0.0120 ±

90 Sediment Deposition

Table A2.3. 7Be Inventory (I) and mass flux () calculation data.

)

/day)

) )

)

(A, (A,

)

2 2

(days)

hickness

(g/cm

Date

, g/cm3)

(h, (h, cm)

dpm/g)

7 7 Inventory , dpm/cm , dpm/cm

 dpm/cm ,

(z, cmbsf) (z, -

7 Activity 7 Activity

(

R N

ection T ection

(I, dpm/cm

(I (I

Mean Mean Activity

Depth in Core in Depth

New Inventory New

Total Inventory Total

Wet Bulk Density Wet

Mass Flux Flux Mass

Residual Inventory Residual

Time Elapsed Elapsed Time

Mass Flux Flux Mass Core S Core Santa Margarita Segment Site 1 0-1 1 1.208 0.157 0.19 1.71 initial

15- 1-2 1 1.001 0.683 0.68 Nov- 2-3 1 1.023 -0.742 0.00 07 3-4 1 1.146 0.731 0.84

13 - Dec- 0-1 1 1.208 -0.155 0.00 0.00 28 1.189 -1.189 0.000

0-1 1 1.208 2.141 2.59 2.99 39 0.000 2.989 0.636 4.704 0.121 21- 1-2 1 1.001 0.312 0.31 Jan- 2-3 1 1.023 -0.448 0.00 08 3-4 1 1.023 0.087 0.09

0-1 1 1.208 2.071 2.50 4.27 38 1.824 2.446 1.276 1.917 0.050 28- Feb- 1-2 1 1.001 1.315 1.32

08 2-3 1 1.023 0.440 0.45

3- 0-1 1 1.001 -0.666 0.00 0.25 34 2.744 -2.495 0.122 20.459 0.602 Apr- 1-2 1 1.023 0.243 0.25 08

0-1 1 1.208 0.995 1.20 1.20 41 0.146 1.056 0.996 1.061 0.026 14- 1-2 1 1.001 -0.744 0.00 May- 2-3 1 1.023 -0.196 0.00 08 3-4 1 1.023 -0.6191 0.00

0-1 1 1.208 0.6250 0.75 1.11 71 0.478 0.632 0.490 1.291 0.018 24- Jul- 1-2 1 1.001 0.3547 0.36

08 2-3 1 1.023 -0.9824 0.00

0-1 1 1.208 1.4248 1.72 3.11 27 0.781 2.333 1.409 1.657 0.061 20- Aug- 1-2 1 1.001 1.3923 1.39

08 2-3 1 1.023 -1.4336 0.00

30 - Sep- 0-1 1 1.208 -1.3572 0.00 0.00 41 1.827 -1.827 0.000

Table A2.3. Continued

)

/day)

) )

)

(A, (A,

)

2 2

(days)

(g/cm

/cm

(g/cm

Date

, g/cm3)

(h, (h, cm)

dpm/g)

7 7 Inventory , dpm , dpm/cm

 dpm/cm ,

(z, cmbsf) (z, -

7 Activity 7 Activity

(

R N

ection Thickness ection

(I, dpm/cm

(I (I

Mean Mean Activity

Depth in Core in Depth

New Inventory New

Total Inventory Total

Wet Bulk Density Wet

Mass Flux Flux Mass

Residual Inventory Residual

Time Elapsed Elapsed Time

Mass Flux Flux Mass Core S Core Santa Margarita Segment Site 2 - 0-1 1 0.982 0.00 0.18 initial 0.3511 - 15- 1-2 1 1.194 0.00 Nov- 0.0199 07 2-3 1 1.140 0.1587 0.18

- 3-5 2 1.160 0.00 0.4501

0-1 1 0.982 0.8194 0.80 0.80 67 0.076 0.729 0.819 0.889 0.013 - 21- 1-2 1 1.194 0.00 Jan-08 0.4125 - 1-2 1 1.194 0.00 0.3433 28 - 0-3 3 0.982 0.4289 1.26 1.26 38 0.491 0.772 0.429 1.801 0.047 Feb-08

3-Apr- 0-1 1 0.982 1.0534 1.03 1.35 34 0.812 0.535 0.658 0.814 0.024 08 1-2 1 1.194 0.2619 0.31

- #DIV/0 #DIV/0 0-1 1 0.982 0.00 0.00 41 0.790 -0.790 0.000 0.4110 ! ! - 14- 1-2 1 1.194 0.00 1.0728 May- - 08 2-3 1 1.140 0.00 0.4046 - 2-3 1 1.140 0.00 0.1276 - #DIV/0 #DIV/0 0-1 1 0.982 0.00 0.00 71 0.000 0.000 0.000 24-Jul- 0.0409 ! ! 08 - 1-2 1 1.194 0.00 0.2138

20- 0-1 1 0.982 0.2334 0.23 0.23 27 0.000 0.229 0.233 0.982 0.036 Aug- - 1-2 1 1.194 0.00 08 0.3920

0-1 1 0.982 0.2832 0.28 3.06 41 0.134 2.922 0.887 3.295 0.080 1-2 1 1.194 1.2755 1.52

30- 2-3 1 1.140 1.1012 1.26 Sep- 08 - 3-4 1 1.160 0.00 0.0884 - 4-5 1 1.142 0.00 4.1774

92 Sediment Bulk Characteristics by Index Period: C, N, P Table A2.4. Sediment bulk characteristics for each index period.

% Index Sample % Total OC:N OC:P N:P Site Organic % Total P % Fines Period Depth N (molar) (molar) (molar) C 0 – 1 cm 1.2 0.13 0.0556 10.8 55.8 5.2 43.9 1 – 2 cm 0.95 0.11 0.0516 10.1 47.6 4.7 48.3 Pre- 2 – 3 cm 0.92 0.12 0.0528 8.9 45.0 5.0 50.3 liminary 3 – 4 cm 1.1 0.13 0.0489 9.9 58.1 5.9 51.5 Sampling 4 – 6 cm 0.98 0.12 0.052 9.5 48.7 5.1 78.3 6 – 8 cm 1.3 0.18 0.0525 8.4 64.0 7.6 81.8 8 – 10 cm 1.0 0.12 0.0494 9.7 52.3 5.4 77.6 0 – 1 cm 1.6 0.22 0.0695 8.5 59.5 7.0 51.1 1 – 2 cm 1.2 0.16 0.0506 8.8 61.3 7.0 50.0 2 – 3 cm 1.0 0.12 0.036 9.7 71.8 7.4 52.0 3 – 4 cm 1.2 0.17 0.024 8.2 129.2 15.7 54.8 Index 4 – 5 cm 0.84 0.13 0.045 7.5 48.2 6.4 55.8 Period 1 - 2.3 0.28 0.025 9.6 237.7 24.8 65.0 Winter 5 – 6 cm 6 – 8 cm 1.9 0.24 0.0801 9.2 61.3 6.6 62.2 8 – 10 cm 1.3 0.20 0.0138 7.6 243.4 32.1 53.2 10 – 12 cm 0.90 0.13 0.0191 8.1 121.7 15.1 12 – 14 cm 1.3 0.14 0.0167 10.8 201.1 18.6 55.1 0 – 1 cm 0.54 0.07 0.0477 9.0 29.2 3.2 31.2 1 – 2 cm 0.34 0.00 0.0394 22.3 0.0 13.3

2 – 3 cm 0.28 0.00 0.0380 19.0 0.0 14.5

Index 3 – 4 cm 0.33 0.00 0.0445 19.2 0.0 15.2 Period 2 - 4 – 5 cm 0.55 0.00 0.0420 33.9 0.0 16.9 Spring 5 – 6 cm 0.00 0.00 0.0554 0.0 0.0 22.6

Segment 1 Segment 6 – 8 cm 1.2 0.13 0.0643 10.8 48.2 4.5 56.7 8 – 10 cm 1.1 0.14 0.0681 9.2 41.7 4.6 55.5 10 – 12 cm 1.1 0.14 0.0633 9.2 44.9 4.9 53.5 0 – 1 cm 0.58 0.04 0.0460 16.9 32.6 1.9 21.0 1 – 2 cm 0.24 0.00 0.0317 19.6 0.0 12.5 2 – 3 cm 0.16 0.00 0.0333 12.4 0.0 8.5 Index 3 – 4 cm 0.15 0.00 0.0298 13.0 0.0 8.2 Period 3 - 4 – 5 cm 0.12 0.00 0.0350 8.8 0.0 9.9 Summer 5 – 6 cm 0.12 0.00 0.0286 10.8 0.0 9.9 6 – 8 cm 0.94 0.11 0.0374 10.0 65.0 6.5 14.5 8 – 10 cm 0.41 0.00 0.0440 24.1 0.0 22.0 10 – 12 cm 0.61 0.06 0.0552 11.9 28.5 2.4 37.0 0 – 1 cm 0.34 0.00 0.4931 1.8 0.0 30.3 1 – 2 cm 0.81 0.09 0.0572 10.5 36.6 3.5 31.9 2 – 3 cm 1.0 0.13 0.0542 8.8 46.9 5.3 55.8 Index 3 – 4 cm 1.3 0.16 0.0639 9.8 54.2 5.5 64.5 Period 4 - 4 – 5 cm 1.2 0.14 0.0633 9.7 47.4 4.9 72.6 Fall 5 – 6 cm 0.95 0.14 0.0575 7.9 42.7 5.4 70.9 6 – 8 cm 0.76 0.12 0.0610 7.4 32.2 4.4 62.7 8 – 10 cm 0.85 0.12 0.0567 8.3 38.7 4.7 63.4 10 – 12 cm 0.32 0.00 0.0380 21.8 0.0 51.7

93 Table A2.4. Continued

% Index Sample % Total OC:N OC:P N:P Site Organic % Total P % Fines Period Depth N (molar) (molar) (molar) C 0 – 1 cm 0.56 0.07 0.0404 9.3 35.8 3.8 20.4 1 – 2 cm 0.45 0.00 0.0342 34.0 0.0 30.0 Pre- 2 – 3 cm 0.25 0.00 0.0245 26.4 0.0 34.4 liminary 0.26 0.00 0.021 32.0 0.0 1.7 Sampling 3 – 5 cm 5 – 7 cm 0.26 0.00 0.022 30.5 0.0 1.6 7 – 9 cm 0.37 0.00 0.0224 42.7 0.0 1.6 0 – 1 cm 0.15 0.00 0.0624 6.2 0.0 1.6 1 – 2 cm 0.15 0.00 0.0627 6.2 0.0 1.7 2 – 3 cm 0.11 0.00 0.0396 7.2 0.0 2.1 Index 3 – 4 cm 0.12 0.00 0.035 8.9 0.0 1.2 Period 1 - 4 – 5 cm 0.10 0.00 0.021 12.3 0.0 1.3 Winter 5 – 6 cm 0.15 0.00 0.05 7.8 0.0 1.7 6 – 8 cm 0.11 0.00 0.095 3.0 0.0 1.2 8 – 10 cm 0.13 0.00 0.084 4.0 0.0 2.6 10 – 12 cm 0.12 0.00 0.031 10.0 0.0 1.6 0 – 1 cm 1.2 0.11 0.0542 12.7 57.2 4.5 23.3 1 – 2 cm 1.8 0.13 0.0253 16.2 184 11.4 26.0 2 – 3 cm 0.46 0.00 0.0259 45.8 0.0 17.4 Index 3 – 4 cm 0.15 0.00 0.0231 16.8 0.0 5.56

Period 2 - 4 – 5 cm 0.24 0.00 0.0281 22.1 0.0 3.44 Spring 5 – 6 cm 0.19 0.00 0.0195 25.1 0.0 4.19 6 – 8 cm 0.09 0.00 0.0112 20.8 0.0 2.56

gment 2 gment 8 – 10 cm 0.14 0.00 0.0239 15.1 0.0 1.36 Se 10 – 12 cm 0.09 0.00 0.0116 20.1 0.0 1.17 0 – 1 cm 0.20 0.00 0.0158 32.6 0.0 1.52 1 – 2 cm 0.2 0.00 0.0261 19.8 0.0 1.70 2 – 3 cm 0.09 0.00 0.0170 13.7 0.0 1.51 Index 3 – 4 cm 0.11 0.00 0.0138 20.6 0.0 0.89 Period 3 - 4 – 5 cm 0.00 0.00 0.0148 0.0 0.0 1.05 Summer 5 – 6 cm 0.00 0.00 0.0101 0.0 0.0 1.43 6 – 8 cm 0.00 0.00 0.0081 0.0 0.0 1.28 8 – 10 cm 0.00 0.00 0.0127 0.0 0.0 1.24 10 – 12 cm 0.00 0.00 0.0084 0.0 0.0 1.54 0 – 1 cm 0.14 0.00 0.0313 11.5 0.0 5.19 1 – 2 cm 0.08 0.00 0.0170 12.2 0.0 1.64 2 – 3 cm 0.00 0.00 0.0159 0.0 0.0 3.87 Index 3 – 4 cm 0.00 0.00 0.0148 0.0 0.0 3.31 Period 4 - 4 – 5 cm 0.00 0.00 0.0120 0.0 0.0 0.83 Fall 5 – 6 cm 0.00 0.00 0.0137 0.0 0.0 2.70 6 – 8 cm 0.00 0.00 0.0238 0.0 0.0 2.26 8 – 10 cm 0.00 0.00 0.0088 0.0 0.0 1.58 10 – 12 cm 0.00 0.00 0.0135 0.0 0.0 2.05

94 Sediment Porewater Concentrations Table A2.5. Porewater constituent analysis for each index period. Constituent values in µM.

Segment 1

NO3 + -2 Depth TDN NH4 NO2 TDP SRP TCO2 S DOC Fe Mn NO2

Bottom 36.0 6.3 8.1 0 4.69 1.8 1180 1.55 183 0.349 3.56 water 0–1 cm 44.9 7.4 2.8 0 5.04 1.6 2770 1.35 290 2.15 7.46 1–2 cm 393 410 3.4 1 5.95 2.8 3830 1.42 900 8.24 27.3 Index 2–3 cm 636 7.4 2.6 0 14.2 14.6 6030 1.35 783 4.48 67.3 Period 1 – 3–4 cm 599 724 3.2 0 59.4 82.4 4610 10.3 738 47.5 65.5 Winter 4–5 cm 597 688 3 0 91.3 95.2 3000 6.82 685 53.7 54.6 1/21/2008 5–6 cm 588 650 2.4 2.2 96.7 105 2120 13.2 653 51.9 51.0 7–8 cm 522 530 8.8 1 95.9 106 1740 8.78 683 37.6 49.1 10–11 cm 310 330 21 0 41.2 50.6 1070 5.74 650 32.2 18.2 13–14 cm 275 318 5.4 0.8 47.4 57.2 1050 5.41 600 26.9 10.4 Bottom 35.5 3.35 12.3 0 2.02 1.5 1060 0 276 1.40 3.50 water 0–1 cm 1370 18.4 3.6 0 105 12.4 971 0.969 1300 129 9.47 1–2 cm 192 9.2 4.6 1 11.6 2.8 1520 0 927 75.2 17.1 Index 2–3 cm 434 292 6.4 0.4 2.64 1.2 2350 0 996 39.4 98.3 Period 2 – 3–4 cm 900 770 6.8 0 0.282 0 2680 0 1930 94.9 237 Spring 4–5 cm 1210 1080 15.6 0 1.43 1 5030 0.277 1360 62.7 162 4/3/2008 5–6 cm 1650 1410 11.4 0 6.43 1.8 5910 0 1290 127 182 7–8 cm 2000 1680 5.4 0 188 110 5670 17.2 1360 448 138 11–12 cm 1520 1160 6.6 0 208 188 4250 378 1090 75.2 52.8 13–14 cm 1160 894 4.8 0 152 10 3270 17.2 997 106 102 Bottom 22.0 1.9 11.7 0 1.43 1 396 0 283 0.492 0.319 water 0–1 cm 0 716 11.8 0 0 127 2550 85.3 595 23.3 29.1 1–2 cm 1070 772 27.6 1.6 135 117 2330 59.9 585 62.7 30.0 Index 2–3 cm 1100 846 24.2 0 124 114 2170 90.1 550 48.3 30.9 Period 3 – 3–4 cm 1210 922 24 0 129 109 2560 135 578 68.0 34.6 Summer 4–5 cm 1460 1190 40.2 0 156 138 3110 181 628 66.3 43.7 7/22/2008 5–6 cm 1570 1290 14.6 0 162 145 3320 591 618 17.9 41.9 6–7 cm 1880 1590 70.4 0 196 168 3580 154 738 25.1 40.0 9–10 cm 1740 1460 43.2 0 178 159.2 3950 54.5 734 60.9 25.5 13–14 cm 1390 1140 49.2 0 172 150 3410 25.3 685 25.1 25.5 Bottom 18.0 2.97 2.33 0.2 0.535 1.1 6.08 0 72.9 2.69 0.328 water 0–1 cm 27.5 17.0 2.8 0 5.31 4.4 2810 0 103 26.9 3.82 1–2 cm 204 242 0 0 37.9 40.8 3680 482 72.5 15.6 12.2 Index 2–3 cm 998 1340 0 0 140 159 3900 5550 200 26.9 21.8 Period 4 – 3–4 cm 1490 1870 0 0 177 232 861 9180 294 34.0 21.8 Fall 4–5 cm 1640 2200 0 0 206 159 4670 8010 313 34.0 27.3 9/29/2008 5–6 cm 1060 2266 0 0 166 171 4130 7360 458 32.2 38.2 7–8 cm 2360 2750 0 0 219 308 0 7430 298 35.8 58.2 10–11 cm 1660 2740 0 0 182 138 0 5050 365 68.0 61.9 13–14 cm 1620 2070 0 0 149 176 0 4240 313 23.3 36.4

95 Table A2.5. Continued

Segment 2

NO3 + -2 Depth TDN NH4 NO2 TDP SRP TCO2 S DOC Fe Mn NO2

Bottom 28.6 3.45 12.3 0 2.14 1.3 1.45 295 0.596 2.55 water 0–1 cm 102.2 4.2 22.8 2.6 6.88 4 321 2.70 693 1.97 1.55 1–2 cm 65.3 5.6 35.8 1.4 6.07 1.6 958 1.28 260 1.34 0.928 Index 2–3 cm 67.7 3.2 27.8 0 2.50 1.2 875 1.55 434 1.18 1.07 Period 1 – 3–4 cm 54.1 4.2 21.6 0 1.28 1.2 919 1.69 423 0.752 0.710 Winter 4–5 cm 5.0 4.4 27 0 0.787 1.4 932 1.42 525 0.752 1.02 1/21/2008 5–6 cm 43.6 4.2 13.8 0 4.13 1.2 809 1.35 585 0.859 0.510 7–8 cm 42.0 5.2 2.8 0 1.4 1.4 642 1.22 448 0.627 0 10–11 cm 33.9 4.6 3.8 0 4.08 2.2 721 1.49 560 0.985 0 14–15 cm 61.7 2.6 31 1.2 5.48 4 777 1.49 618 0.394 0 Bottom 39.2 5.5 14.8 0 3.58 2.07 1630 0 470 1.32 8.01 water 0–1 cm 36.9 3 11.2 0 1.08 0 585 0 467 3.40 0.158 1–2 cm 57.6 2 21.6 0 0.293 0 791 0 485 3.76 0.162 Index 2–3 cm 53.7 5.2 21 0 1.55 1.6 860 0 672 4.30 0.076 Period 2 – 3–4 cm 52.0 1.6 18.4 0 1.33 1.6 850 0 1150 2.15 0.075 Spring 4–5 cm 49.8 4.4 20.6 0 0.527 1.4 907 0 747 3.40 0.124 4/3/2008 5–6 cm 54.7 3.8 20.6 0 0.121 0 853 0 504 1.97 0.098 7–8 cm 52.2 13.2 20.8 2.8 0.880 0 817 0 785 2.33 0.510 10–11 cm 71.9 12.8 40 15.2 0.112 0 844 0 824 2.69 17.5 13–14 cm 136 77 23.9 3 1.55 1.7 882 0 630 5.91 124 Bottom 29.5 3.5 4.6 0.65 5.29 4.35 699 0.262 450 0.716 0.528 water 0–1 cm 66.7 45.8 15.0 0 17.7 16 795 1.01 473 19.7 49.1 1–2 cm 87.3 58 19.0 0 32.5 32.2 789 0.794 415 34.0 47.3 Index 2–3 cm 155 101 13.8 0 44.6 44.6 948 0.902 410 19.7 43.7 Period 3 – 3–4 cm 138 92.2 12.4 0 28.9 22.6 927 71.9 430 9.94 21.8 Summer 4–5 cm 151 104 13.0 0 34.6 29.2 933 68.0 433 8.42 38.2 7/22/2008 5–6 cm 171 105 7.8 0 42.3 47 1070 81.0 433 6.45 49.1 7–8 cm 196 153 7.4 0 52.3 47 1160 55.8 398 8.24 61.9 10–11 cm 165 120 9.2 0 36.3 49.2 1080 5.49 435 49.2 69.2 13–14 cm 131 97.2 10.8 0 27.6 44 1080 2.20 440 51.9 65.5 Bottom 219.5 24.8 1.7 0 0 6.24 7.3 702 0 2.06 5.82 water 833 0–1 cm 103 60.4 0 0 22.3 24 568 62.4 90 5.01 104 1–2 cm 126 82.6 0 0 26.6 27 635 90.2 82.5 6.98 51.0 Index 2–3 cm 25.5 22.8 0 0 6.67 14.3 456 7.66 87.5 43.0 44.0 Period 4 – 3–4 cm 69.0 62.4 3 0 15.9 27.3 554 18.3 204 7.70 45.5 Fall 4–5 cm 137 109 2.7 0 45.0 42.1 553 4.39 92.5 25.1 71.0 9/29/2008 5–6 cm 124 126 0 0 33.6 49.2 683 0.375 75.0 43.0 96.5 7–8 cm 125 168 2 0 36.4 59.8 769 1.89 130 35.8 96.5 10–11 cm 192 176 2.4 0 64.0 57.2 912 4.21 67.5 23.3 95.0 13–14 cm 181 147 2 0 64.6 52.2 659 16.8 138 9.49 76.4

96 Water Column Transect Data Table A2.6. Transect data for each index period during ebb tide (constituents are in mmol/L, except for chlorophyll a, which is in μg/l).

NO3 + Chl a Site # TN TDN NH4 NO2 TP TDP SRP TSS NO2 1 216.3 315.3 3.78 130.0 0.571 3.52 3.71 3.10 42.3 10.0 2 92.3 185.0 9.92 133.0 0.714 3.07 3.26 2.81 34.3 8.5 3 497.5 47.3 4.5 4 200.0 224.8 66.8 193.9 0.928 2.55 3.36 2.19 3.3 7.1 5 231.6 403.3 3.00 207.9 1.21 3.75 3.68 3.81 9.1 -1.0 Index 6 155.1 324.8 108.0 218.0 1.00 2.36 3.80 1.61 12.0 5.3 Period 1 7 Winter 1.78 106.0 0.571 2.29 2.58 3.19 45.0 6.2 8 197.6 1136 2.42 226.0 1.21 3.75 3.52 3.71 8.3 6.2 9 181.6 395.1 2.18 190.5 0.785 2.58 3.94 7.10 7.5 6.2 10 217.0 394.6 1.43 229.0 1.00 3.52 3.81 2.29 4.7 3.6 11 122.4 532.9 2.43 171.0 0.785 2.78 5.04 1.81 13.0 4.5 12 161.8 408.7 70.5 224.0 1.50 2.42 3.78 2.39 9.7 -1.0 1 54.6 79.0 3.71 22.4 0.428 3.87 3.16 2.90 3.0 13.4 2 52.2 64.3 3.50 19.2 0.286 3.61 3.32 3.09 3.7 9.3 3 52.1 75.4 3.43 20.3 0.357 4.22 3.84 3.29 3.0 9.3 4 49.3 73.7 2.93 26.4 0.500 4.22 4.03 3.61 2.7 12.7 5 62.9 76.3 2.00 32.1 0.571 4.39 4.10 3.29 7.7 12.9 Index 6 55.4 75.0 2.21 30.7 0.500 4.13 3.77 3.00 3.3 42.7 Period 2 7 Spring 62.0 66.9 1.93 31.9 0.500 4.08 3.72 3.45 7.3 20.0 8 54.9 56.7 2.43 32.4 0.500 4.29 4.39 3.39 2.3 10.2 9 52.4 36.5 2.00 32.1 0.500 4.16 4.19 3.48 3.1 11.3 10 53.1 51.1 1.78 30.4 0.500 3.45 3.61 3.29 2.4 10.2 11 56.7 45.1 1.43 34.2 0.500 3.90 4.03 3.39 1.7 10.2 12 46.8 39.5 1.07 35.5 0.500 3.87 3.81 3.00 2.1 10.7 1 11.4 197.8 12.8 1.30 0.000 0.736 0.588 0.200 2.3 2.7 2 13.1 47.6 83.7 1.60 0.000 0.610 0.604 0.900 3.2 2.2 3 11.2 293.4 0.00 0.00 0.000 0.488 0.694 0.400 2.3 2.2 4 9.26 69.2 3.10 0.00 0.000 0.839 0.965 0.600 3.0 2.7 5 68.9 1131 11.8 2.40 0.200 1.09 0.962 1.00 3.5 4.9 Index 6 23.4 96.3 19.1 6.70 0.400 1.48 1.23 1.30 5.3 10.2 Period 3 7 Summer 31.1 87.4 44.3 6.20 0.500 1.90 1.97 1.40 4.0 10.1 8 38.6 91.3 36.4 10.4 0.850 2.92 1.99 1.80 4.0 12.9 9 6.55 5.5 16.9 10 45.3 141.9 44.4 16.8 1.30 2.89 2.07 2.20 6.3 13.4 11 52.9 146.0 106.0 20.2 1.40 3.49 3.36 2.70 7.0 14.7 12 49.8 116.5 17.2 16.8 1.40 3.52 3.74 2.10 3.3 14.7 1 46.9 49.2 18.5 2.20 0.300 1.99 1.74 1.10 3.7 1.6 2 20.3 38.8 2.90 0.600 0.000 2.18 1.71 0.900 6.0 2.2 3 24.9 42.8 1.60 0.000 0.000 2.29 1.88 1.10 4.5 3.6 4 28.2 24.9 0.500 0.000 0.000 4.18 3.58 2.70 2.7 8.0 5 43.1 36.3 0.900 3.20 0.000 4.63 3.95 3.10 1.7 4.9 Index 6 36.4 49.1 2.00 1.90 0.200 3.45 3.01 2.60 6.0 5.3 Period 4 7 35.3 56.9 1.90 1.50 0.000 4.97 4.68 3.90 3.0 6.2 Fall 8 51.2 56.7 0.550 3.15 0.200 6.27 6.26 4.60 3.2 3.4 9 35.5 56.6 8.21 11.7 10.1 10 39.7 57.7 0.500 0.000 0.000 9.28 9.54 7.60 4.0 6.2 11 38.7 36.9 0.100 0.000 0.000 11.2 10.4 8.20 2.4 4.5 12 44.3 32.6 0.500 0.000 0.000 12.4 12.5 11.2 4.7 5.8

97 Table A2.7. Transect data for each index period during flood tide.

NO3 + Chl a Site # TN TDN NH4 NO2 TP TDP SRP TSS NO2 1 31.1 31.9 0.21 1.85 0.143 0.161 0.048 0.613 6.4 13.7 2 158.6 566.4 1.99 157.9 0.571 1.10 4.81 2.80 7.5 5.0 3 182.3 169.8 98.76 167.9 0.785 3.23 2.64 3.81 5.0 6.2 4 161.3 610.3 120.0 138.0 0.714 2.00 2.03 4.00 6.7 86.3 5 280.2 188.6 78.1 212.9 1.00 2.81 3.58 1.48 8.0 5.3 Index 6 248.1 400.0 0.714 81.8 0.428 3.52 3.55 3.19 8.3 8.0 Period 1 7 Winter 206.9 655.6 14.1 202.9 1.07 3.06 1.80 41.7 6.7 8 135.0 403.3 10.8 182.9 1.07 4.71 4.45 3.90 9.0 1.9 9 192.2 721.2 1.93 186.9 0.928 3.29 5.32 2.85 10.0 1.8 10 176.5 213.0 1.28 181.9 1.21 4.19 3.19 3.71 10.3 4.7 11 151.8 193.6 1.78 116.0 0.500 4.58 2.55 3.19 9.0 7.7 12 251.1 400.8 2.21 52.8 0.214 4.00 3.42 0.484 10.5 7.1 1 21.9 15.9 1.28 3.28 -0.071 1.16 0.743 0.710 8.0 10.2 2 42.5 54.0 4.21 16.92 0.428 3.16 2.87 2.48 7.3 16.0 3 50.4 54.4 3.28 16.71 0.286 3.45 3.24 2.80 20.2 28.9 4 59.6 75.8 2.49 27.6 0.428 4.39 4.16 3.19 9.0 15.4 5 50.8 76.9 1.49 32.9 0.500 3.61 3.93 3.19 3.5 14.2 Index 6 58.6 51.6 1.57 29.7 0.428 3.51 3.87 3.19 9.7 10.2 Period 2 7 Spring 55.7 49.3 1.21 29.9 0.428 4.00 3.84 3.09 5.3 11.1 8 59.9 81.5 1.42 31.1 0.500 4.32 3.87 2.80 4.7 19.6 9 64.9 60.8 1.49 31.6 0.428 3.68 4.13 3.00 2.0 11.1 10 71.3 63.4 1.21 32.9 0.428 4.13 4.26 3.09 0.7 11.6 11 60.9 58.6 0.928 33.1 0.286 3.61 3.93 3.19 3.4 11.1 12 62.3 56.4 1.00 32.7 0.286 3.94 3.71 3.39 5.4 11.6 1 34.0 41.3 0.800 9.50 0.500 1.71 1.65 1.00 3.4 5.6 2 66.8 50.0 0.700 20.5 0.900 3.33 2.96 1.70 3.5 7.1 3 43.0 39.3 1.00 6.00 0.600 4.27 3.43 2.20 4.0 6.2 4 42.5 45.6 0.600 9.00 0.900 3.91 1.69 2.30 12.3 15.5 5 40.3 32.5 2.10 7.10 1.50 5.06 3.19 5.20 9.5 9.3 Index 6 33.1 2.80 7.10 1.50 4.65 4.14 4.10 4.1 7.6 Period 3 7 Summer 56.1 64.9 4.20 20.6 2.00 6.53 7.06 6.20 5.5 11.1 8 45.9 38.9 6.90 1.00 0.700 7.98 7.47 7.80 2.8 8.5 9 42.2 43.6 6.00 0.600 0.500 7.73 7.21 6.95 7.5 7.3 10 36.5 43.7 2.50 0.000 0.300 6.29 6.42 8.80 13.5 8.9 11 35.2 39.0 0.200 0.000 0.200 7.58 6.84 8.90 4.0 12.0 12 40.9 33.8 0.900 0.000 0.300 8.29 7.01 9.10 3.0 12.9 1 10.7 8.4 0.400 0.000 0.000 0.96 1.02 0.300 68.5 1.8 2 14.4 12.5 0.000 0.000 0.000 1.61 1.33 0.600 6.3 3.6 3 13.5 31.6 1.10 0.000 0.000 1.29 0.904 0.600 13.7 3.1 4 47.5 20.2 0.200 0.000 0.000 4.56 3.91 2.70 2.5 6.7 5 33.2 44.9 0.500 0.000 0.000 4.87 3.86 3.30 3.0 8.9 Index 6 34.6 29.6 1.60 0.000 0.000 6.07 5.30 3.40 8.0 10.7 Period 4 7 49.6 51.1 3.60 4.70 0.900 6.23 4.98 4.10 4.2 2.2 Fall 8 34.1 31.0 0.500 0.000 0.000 6.83 7.01 5.30 1.3 5.3 9 43.0 34.3 0.400 0.000 0.000 12.7 5.472 4.80 3.9 5.8 10 43.5 41.2 0.400 0.000 0.000 13.3 12.9 11.0 4.3 4.5 11 54.7 47.8 0.200 0.000 0.000 16.7 14.8 11.7 4.0 5.3 12 43.9 65.1 0.700 0.000 0.000 18.6 16.8 14.9 3.7 3.1

98 Primary Producer Biomass and/or Percent Cover Table A2.8. Means and standard deviations of suspended chlorophyll a and benthic chlorophyll a concentrations during each index period. Mean Suspended Chlorophyll a Index Period Site 3 (mg/m ) 1 Winter 3.65 ± 0.96 2 Spring 1.91 ± 0.17 Segment 1 3 Summer 10.95 ± 1.63 4 Fall 4.76 ± 0.37 1 Winter 5.49 ± 0.34 2 Spring 1.92 ± 0.76 Segment 2 3 Summer 5.60 ± 0.44 4 Fall 1.01 ± 0.01

Table A2.9. Macroalgae total percent cover and biomass by species during each index period. Dry Biomass (g/m2) Total % Cover Site Date Ulva intestinalis Ulva expansa Cyanobacteria Total Biomass avg SE avg SE avg SE avg SE avg SE 1/22/08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Segment 4/11/08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1 7/21/08 46.53 43.48 7.76 5.26 0.00 0.00 54.29 48.19 81.67 16.98 9/29/08 0.00 0.00 175.10 93.49 63.27 44.54 238.37 88.19 100.00 0.00

1/22/08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Segment 4/11/08 0.56 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 7/21/08 0.00 0.00 14.69 9.14 0.00 0.00 14.69 9.14 33.33 12.64 9/29/08 0.41 0.41 40.82 12.07 0.00 0.00 41.22 12.30 98.33 1.11

99 Rates of Exchange Between Surface Waters and Sediments – Benthic Flux Table A2.10. Benthic fluxes by index period and light/dark regime Index Regime Type DO TCO TDN TDP DOC Fe Mn NH NO SRP Period 2 4 3 avg 28.7 -145 -20.97 0.40 -729 -0.46 0.33 15.95 -32.49 1.27 light stdev 120 53.3 30.5 2.29 539. 0.15 0.56 21.44 38.73 2.98 1 Winter avg -164 183 -4.85 0.78 -615 -0.17 0.03 9.01 -20.18 0.20 dark stdev 138 109 19.79 2.01 770 0.04 0.37 12.17 28.16 0.51 avg 234 -78.4 -16.78 -1.16 134 -0.07 -0.35 -0.25 0.94 -0.02 light

stdev 33.7 23.15 0.11 284 0.10 0.34 0.24 4.14 0.03 2 Spring avg -11.0 37.3 -12.81 -0.41 -217 -0.14 0.24 -0.33 -15.83 -0.11 dark stdev 10.5 0.68 7.76 1.55 455 0.19 0.87 0.69 5.93 0.68 avg 33.4 -60.7 3.03 6.41 343 -1.14 -0.54 32.15 -34.79 3.70 light

3 stdev 24.2 28.01 1.06 229 1.51 1.52 44.12 3.13 5.24 Segment Site 1 Site Segment Summer avg -85.1 38.0 7.62 1.72 257 0.81 -0.24 23.81 -16.67 1.33 dark stdev 4.41 3.03 0.21 238 0.64 0.14 19.94 1.56 1.57 avg 29.6 -21.2 2.95 0.81 62.8 -0.58 0.06 6.75 -4.23 0.60 light stdev 38.0 5.26 5.45 0.22 31.1 0.33 0.17 6.81 1.88 0.38 4 Fall avg -28.9 12.7 1.55 0.04 94.6 -0.06 0.23 3.59 -0.38 -0.01 dark stdev 3.81 4.59 2.10 0.66 133 0.26 0.05 2.99 0.59 0.11

avg 57.4 -6.06 -0.47 0.51 -144 0.10 0.00 0.08 -1.15 -0.39 light stdev 4.58 4.70 2.58 0.98 1229 0.24 0.09 0.30 0.42 0.56 1 Winter avg -14.2 10.8 -1.25 0.05 -153 -0.10 -0.07 -0.14 -0.04 0.08 dark stdev 19.1 0.57 0.92 1.02 733 0.05 0.10 0.72 0.06 0.40 avg 48.1 -35.4 -0.90 0.36 -81.0 0.29 -0.05 0.01 -3.40 0.19 light

stdev 36.8 5.72 0.98 0.13 90.9 0.04 0.55 0.45 1.82 0.32 2 Spring avg -3.14 13.3 1.23 -0.14 157 0.08 -0.03 0.01 1.33 -0.35 dark stdev 1.47 7.03 1.49 0.16 352 0.28 0.05 0.00 0.11 0.47 avg 69.4 -62.5 3.91 0.10 -5.74 0.91 -0.46 0.91 -0.18 0.68 light

3 stdev 84.43 5.53 0.14 8.12 1.28 0.65 1.29 0.26 0.96 Segment Site 2 Site Segment Summer avg -37.9 61.50 1.10 -0.60 -119 0.35 -1.56 0.94 -0.20 0.12 dark stdev 11.5 1.05 2.17 0.29 2.40 0.79 0.07 2.20 0.13 0.37 avg -30.0 34.6 -0.82 -3.80 -431 -6.12 -2.26 1.69 -0.05 0.53 light stdev 63.3 203 2.86 0.69 1071 4.43 2.53 2.31 0.50 2.17 4 Fall avg -93.6 66.8 1.78 4.59 516 -4.99 0.00 -2.12 -0.52 0.27 dark stdev 7.63 44.8 2.30 0.24 286 7.32 0.00 1.47 0.78 0.98

100 Data on Additional Factors Controlling Benthic Flux Table A2.11. Number of benthic infauna in each chamber by index period, along with chamber

light/dark regime, site average, and standard deviation.

) ) ) ) ) ) )

)

2 2 2 2 2 2 2 2

Index Chamber

Period m duals/

Total Total

Other Other

Mollusks Mollusks

Capitellids Capitellids

Polychaetes Polychaetes Polychaetes

Crustaceans Crustaceans

Total Infauna Infauna Total

Oligochaetes Oligochaetes

(individuals/ m (individuals/ m (individuals/ m (individuals/ (indivi m (individuals/ m (individuals/ m (individuals/ m (individuals/

Chamber 1 (light) 0 0 0 0 0 509 0 509 Chamber 2 (dark) 0 0 509 0 0 0 0 1019 Chamber 3 (light) 0 0 0 0 0 0 0 509 1 Winter Chamber 4 (dark) 0 0 0 0 0 0 0 0 Average 0 0 127 0 0 127 0 509 Standard Deviation 0 0 255 0 0 255 0 416 Chamber 1 (light) 0 0 0 0 0 0 0 0 Chamber 2 (dark) 0 0 0 0 509 0 0 1019 Chamber 3 (light) 0 0 1019 0 0 0 0 1019 2 Spring

Chamber 4 (dark) 0 0 1528 0 0 509 0 2037

Average 0 0 637 0 127 127 0 1019 Standard Deviation 0 0 764 0 255 255 0 832 Chamber 1 (light) 0 0 0 0 3056 0 0 3056

Chamber 2 (dark) 509 0 509 0 1528 0 509 3056 Segment 1 Segment Chamber 3 (light) 0 0 0 509 14260 0 0 14770 3 Summer Chamber 4 (dark) 0 0 509 0 10186 0 0 11205 Average 127 0 255 127 7257 0 127 8021 Standard Deviation 255 0 294 255 6003 0 255 5916 Chamber 1 (light) 0 0 0 0 0 0 0 509 Chamber 2 (dark) 0 0 509 0 0 0 0 509 Chamber 3 (light) 0 0 509 0 0 0 0 509 4 Fall Chamber 4 (dark) 0 0 0 0 0 0 0 0 Average 0 0 255 0 0 0 0 382 Standard Deviation 0 0 294 0 0 0 0 255 Chamber 1 (light) 0 0 0 0 0 0 0 1019 Chamber 2 (dark) 0 0 0 0 0 509 0 509 Chamber 3 (light) 0 0 0 0 0 0 0 0 1 Winter Chamber 4 (dark) 0 0 0 0 0 0 0 509 Average 0 0 0 0 0 127 0 509 Standard Deviation 0 0 0 0 0 255 0 416 Chamber 1 (light) 0 0 0 0 0 2037 0 2546 Chamber 2 (dark) 0 0 0 0 0 0 0 0 Chamber 3 (light) 0 0 0 0 0 2037 0 2037 2 Spring

Chamber 4 (dark) 0 0 0 0 0 1528 0 1528

Average 0 0 0 0 0 1401 0 1528 Standard Deviation 0 0 0 0 0 964 0 1100 Chamber 1 (light) 2037 3056 509 4074 2037 0 5093 13751

Chamber 2 (dark) 0 1528 0 1019 1528 1528 1528 6112 Segment 2 Segment Chamber 3 (light) 2546 509 509 1019 0 509 3056 5093 3 Summer Chamber 4 (dark) 3056 1019 1528 2546 1019 0 4074 11205 Average 1910 1528 637 2165 1146 509 3438 9040 Standard Deviation 1339 1100 641 1463 870 720 1521 4124 Chamber 1 (light) 1019 1528 509 21900 2037 0 2546 29539 Chamber 2 (dark) 0 1019 509 0 3565 0 1019 8149 Chamber 3 (light) 509 509 0 1019 3056 0 1019 5602 4 Fall Chamber 4 (dark) 0 509 0 0 509 0 509 1528 Average 382 891 255 5730 2292 0 1273 11205 Standard Deviation 488 488 294 10791 1347 0 882 12524

101 Appendix 3 - Graphs of Segment 1 and Segment 2 2007-2008 Continuous Data (From CDM, Inc. 2009)

Water Level (m)

-2 12/1/200740 2/1/2008 4/1/2008 6/1/2008 8/1/2008 10/1/2008 X Data 30

Salinlity (ppt) 0

12/1/200720 2/1/2008 4/1/2008 6/1/2008 8/1/2008 10/1/2008 X Data 15

Dissolved Oxygen

Dec-07 Feb-08 Apr-08 Jun-08 Aug-08 Oct-08 Time

Figure A3.1. Continuous water level, salinity, and dissolved oxygen data over December 2007- October 2008 for Segment One (upstream; CDM 2009).

102 12

Water Level (m)

-2 12/1/200740 2/1/2008 4/1/2008 6/1/2008 8/1/2008 10/1/2008 X Data 30

Salinlity (ppt) 0

12/1/200720 2/1/2008 4/1/2008 6/1/2008 8/1/2008 10/1/2008 X Data 15

Dissolved Oxygen

Dec-07 Feb-08 Apr-08 Jun-08 Aug-08 Oct-08 Time

Figure A3.2. Continuous water level, salinity, and dissolved oxygen data over December 2007- October 2008 for Segment Two (downstream; CDM 2009).

103